Keywords: Navigation, Range Sensing, Surveillance Systems
Abstract: This paper describes a new approach to extract planar features from 3D range data captured by a range imaging sensorthe SwissRanger SR-3000. The focus of this work is to segment vertical and horizontal planes from range images of indoor environments. The method first enhances a range image by using the surface normal information. It then partitions the Normal Enhanced Range Images (NERI) into a number of segments using the Normalized-Cuts (N-Cuts) algorithm. A least-square plane is fit to each segment and the fitting error is used to determine if the segment is planar or not. From the resulting planar segments, each vertical or horizontal segment is labeled based on the normal of its least-square plane. A pair of vertical or horizontal segments is merged if they are neighbors. Through this region growing process, the vertical and horizontal planes are extracted from the range data. The proposed method has a myriad of applications in navigating mobile robots in indoor environments.

Keywords: Sonars, Range Sensing
Abstract: Advanced sonar systems produce both accurate range and bearing measurements rather than just range alone as in conventional systems. Previous advanced sonar rings do not process incoming echo data as it arrives, but only after a completed measurement cycle and only on limited data samples that are above a noise floor threshold. The system described in this paper can process all echo data, as it is produced, with full matched filtering tuned to each receiver on all echo samples directly implemented in hardware. This minimises measurement latency, important for real time robotics applications and also provides optimal arrival time estimates due to the matched filters. Previous systems have used sequential firing of many transmitters around the ring to prevent interference between transmitters or used different pulses fired simultaneously. This paper presents a single transmitter solution where a reflector disperses a single ultrasonic pulse evenly around the sonar ring. Processing is performed with a dedicated hardware data processing architecture implemented with a Field Programmable Gate Array to achieve the desired real time performance. The system reports range and bearing results at a rate of 30 measurement cycles a second in a full 360 degree coverage to ranges up to 4 metres with the prototype processing over 4.9 giga-arithmetic operations per second. Experimental results are presented that show the performance of the system is suitable for high speed mapping and localisation applications.

Keywords: Range Sensing, Computer Vision
Abstract: In this paper, we present a new algorithm for the alignment of two 3D scans. The approach uses a region-based matching technique. We make no assumptions about the initial position of the scans. Regions are described by a probability density function (pdf) computed from low dimensional surface descriptors (curvature or normal cone). The algorithm allows registering directly raw noisy data, possibly with the presence of outliers, without any pre-processing, such as filtering, denoising, or reconstruction. Region correspondence is found using similarity function based on the comparison of regions pdf and under geometry constraints. Results on raw scan data sets are presented to illustrate and evaluate the algorithm.

Keywords: Range Sensing, Localization, Marine Robotics
Abstract: Fine-grained (sub-meter) ranging and localization is critical to the deployment of dense, mobile sensor networks in aquatic environments. However, such a task is faced with a number of challenges, including noisy underwater environments, limitation on size and complexity of localization hardware, and constraints on computing capabilities of sensor platforms. In this paper we present a sliding-window discrete Fourier transform (DFT)-based algorithm for precise detection of the arrival of a monotone acoustic signal, as a key enabling step in measuring the time of flight (TOF) of the acoustic signal for localization of the sensor node. The algorithm accommodates the rise dynamics of the signal and compensates for the latency in detection given the signal model, detection threshold, and steady-state signal amplitude. The algorithm is implemented onboard a small biomimetic robotic fish, and experiments in an indoor pool have shown that the proposed method results in an underwater ranging error of 1.4 wavelengths (74.3 cm), and is thus promising for localization of dense aquatic networks. The proposed method has also shown robustness in comparison with other tested methods including a matched filter-type method.

Keywords: Rehabilitation Robotics, Force and Tactile Sensing, Cognitive Human-Robot Interaction
Abstract: To develop a gait rehabilitation robot for hemiplegic patients, quantitative evaluations of patient ability is needed. Patient’s walk phase, which includes time balance of stance and swing legs, is one of the most useful indexes. However, conventional methods measuring walk phase require laborious preparations. In this paper, a novel algorithm estimating walk phase on a treadmill by observing DC motor current is proposed. In comparison of this algorithm and conventional methods, it was verified that the proposed algorithm had as the same accuracy as foot switch. Moreover, the proposed algorithm could estimate stance phase in 0.2 (s) errors between measurements of force plate mostly (4 out of 5 healthy subjects). However, result from the 5th subject showed that the proposed algorithm had erroneously identified stance phase as swing phase when little body weight loaded on leg. This characteristic is often observed in hemiplegic gait. Therefore, the proposed algorithm might need improvement of motor current threshold. However, this algorithm had capable of estimating the time of loading body weight on leg, and thus could be useful as a quantitative evaluation tool.

Keywords: Rehabilitation Robotics, Physical Human-Robot Interaction
Abstract: A legged locomotor device for paraplegics have been attempted to improve their ADL and to prevent some complications. A stride control of the system based on the user's intension is important to coordinate the voluntary movements of the user and the assisted movements of the paralyzed legs. In this paper, we propose a human interface with a walker to control the stride length of a legged locomotor device. Assuming that a intended stride is equal to a distance of the preceding movement of the walker, we developed a human interface estimating the movement distance of the walker, where the distance is calculated by polynomial fitting for the acceleration of the movement. In this study, we examine the proposed human interface from the measurement experiments of gait movements, and report the following results: (1) estimation accuracy by polynomial fitting method, and (2) feasibility of the adjustment of stride length using the proposed method. These results suggest that the proposed human interface is effective to adjust the stride length of a legged locomotor device.

Keywords: Social Human-Robot Interaction, Medical Robots and Systems, Force Control
Abstract: We aim at realization of a “user-friendly walking assist device” to support the life of the elderly, the work operation of production, and others. Based on a biomedical engineering analysis, we developed a new walking assist device with a concept to reduce the floor reaction force of a user of the device. The device comprises an axis layout in which expansion and contraction mechanisms disposed on the right and left are connected to a seat at a single point, a device layout in which the device is disposed along the inner side of the user’s legs, and a mechanism that utilizes a circular arc-shaped rail. With these original layouts and mechanisms, we achieved a walking assist device that can be put on and taken off easily without the need to fasten the device to a user’s body, and that can always maintain the assist force vector in the direction from the center of pressure of floor reaction force to the center of gravity of the user’s body by using only two actuators. The device can reduce the load on leg muscles and joints in various movements and postures. It was confirmed that the device has an assist effect of reducing the user’s leg muscle activities as well as the user’s total body energy consumption when the user climbs stairs or performs a squat exercise.

Keywords: Rehabilitation Robotics, Physical Human-Robot Interaction, Haptics and Haptic Interfaces
Abstract: Robotic devices able to train both reaching and manipulation are often large and complex and thus not suitable for decentralized use at home or in local rehabilitation centers. This paper describes a compact device with only three degrees of freedom (DOF) to train reaching and manipulation critical to activities of daily living. The design considers only the DOF necessary to train tasks such as pick-and-place of objects, drinking, eating and knob manipulation, based on lowdimensional synergies used in these tasks. Specifications from measured biomechanical parameters yield safety and suitable performance. A prototype demonstrates some of the resulting functions and therapeutic possibilities offered by this design.

Keywords: Medical Robots and Systems
Abstract: In recent years there has been an ever increasing amount of research and development of technologies and methods to improve the quality and the performance of advanced surgery. In other fields, such as laparoscopy, several training methods and metrics have been proposed, both to improve the surgeon’s abilities and also to assess her/his skills. For Neurosurgery, however, the extremely small movements and sizes involved have prevented until now the development of similar methodologies and systems. In this paper we present the development of an ultra-miniaturized Inertial Measurement Unit and its application for the evaluation of the performance in a simple pick and place scenario. This analysis is a preliminary yet fundamental step to realize a better training/evaluation system for neurosurgeons, and to objectively evaluate and understand how the neurosurgery is performed.

Keywords: Medical Robots and Systems, Grasping, Path Planning for Manipulators
Abstract: This paper considers robotic automation of a common emph{surgical retraction} primitive of exposing an underlying area by grasping and lifting a thin, 3D, possibly inhomogeneous layer of tissue. We present an algorithm that computes a set of stable and secure grasp-and-retract trajectories for a point-jaw gripper moving along a plane, and runs a 3D finite element (FEM) simulation to certify and assess the quality of each trajectory. To compute secure candidate grasp locations, we use a continuous spring model of thin, inhomogeneous deformable objects with linear energy potential. Experiments show that this method produces many of the same grasps as an exhaustive optimization with an FEM mesh, but is orders of magnitude cheaper: our method runs in O(v log v) time, where v is the number of veins, while the FEM computation takes O(p n³) time, where n is the number of nodes in the FEM mesh and p is the number of nodes on its perimeter. Furthermore, we present a constant tissue curvature (CTC) retraction trajectory that distributes strain uniformly around the medial axis of the tissue. 3D FEM simulations show that the CTC achieves retractions with lower tissue strain than circular and linear trajectories. Overall, our algorithm computes and certifies a high-quality retraction in about one minute on a PC.

Keywords: Haptics and Haptic Interfaces, Medical Robots and Systems
Abstract: In this paper, we present the design of a 7 degrees-of-freedom (DOF) Haptic Interface for applications in Minimally Invasive Surgery (MIS). The design of the interface is based on an existing dual-panthograph Haptic Wand and is capable of position and force reflection in three translational, three rotational DOF and grasping motion. The paper presents the implementation of a novel cable driven differential transmission to include the yaw and grasping force reflection to the interface. The kinematic and dynamic properties of the interface are characterized and presented. Experimental results demonstrate that the device is capable of high-force reflection with good transparency.

Keywords: Medical Robots and Systems, Kinematics, Parallel Robots
Abstract: In biomedical research it is difficult to perceive tumors or cells and perform biopsies manually. Robotics technology can offer a reliable solution for accurate needle insertion. A novel 5 degrees of freedom (DOF) robot for inserting needles into small animal subjects was developed. The robot can realize dexterous alignment of the needle using two parallel mechanisms, and has a syringe mechanism to insert needles to subjects. Operations on small animals require high accuracy positioning during needle insertion. In this paper, kinematic calibration of the 5 DOF robot using an optical tracker as an external sensor is performed to enhance accuracy of the system.

Keywords: Dynamics, Field Robots
Abstract: An unmanned ground vehicle with the ability to change directions without a significant loss in speed would have superior mobility in confined spaces and tight corridors compared to Ackerman-steered or skid-steered vehicles. Omnidirectional vehicles, which can move in any planar direction regardless of their current kinematic pose, inherently have this capability. However, most omnidirectional vehicle designs are not practical for outdoor use because they are based on specialized wheels that can easily become clogged with dirt and debris. This paper presents a dynamic model of an omnidirectional UGV designed to operate in outdoor, real-world environments at speeds high enough to excite the dynamics of the vehicle. The analysis includes derivation of vehicle's equations of motion and a control strategy using inverse dynamics. Simulation results are shown to validate the model.

Keywords: Wheeled Robots, Service Robots, Mechanism Design
Abstract: In this paper, we present the mechanical design of a compact magnetic wheeled robot – with the goal to do inspection and vibration measurements in the housings of large generators and similar environments in power plants. After a detailed analysis of the specifications in this application, we present a new vehicle structure that allows for passing sharp concave corners – even with low friction coefficient between wheels and surface – and without using an additional active DOF. The advantages of this structure and the core parameters for its optimization are described in a quasi-static 2D calculation model. A prototype was implemented and successfully tested both in laboratory and real environments. The paper concludes pointing out the future improvements for a final industrial version.

Keywords: Wheeled Robots, Recognition, Space Robotics
Abstract: Identifying planetary soil parameters is not only an important scientific goal, but also necessary for exploration rover to optimize its control strategy and realize high-fidelity simulation. An improved wheel-soil interaction mechanics model is introduced, and it is then simplified by linearizing the normal stress and shearing stress to derive closed-form analytical equations. Eight unknown soil parameters are divided into three groups. The highly complicated coupled equations, each of which includes all the unknown soil parameters, are then decoupled. Each decoupled equation contains one or two groups of soil parameters, making it feasible to make a step-by-step identification of all the unknown parameters that characterize the soil. Wheel-soil interaction experiments were performed for six kinds of wheels with different dimensions and wheel lugs on simulated planetary soil. Soil parameters are identified with the measured data to validate the method, which are then used to predict wheel-soil interaction forces and torque, with a less than 10% margin of error. The improved model, decoupled analytical model, and soil-characterizing method can play important roles in the development of both the planetary exploration rovers and the terrestrial vehicles.

Keywords: Wheeled Robots, Motion Control, Grasping
Abstract: The paper develops a method for analyzing and improving by control obstacle clearance capacity of articulated multi-wheeled rovers. On uneven ground surface, load and traction force distributions through the wheel/ground contact system are highly coupled. They are both conditioned by the global equilibrium of the mechanical system and the contact stability constraints. The optimal traction force distribution problem is formulated here as a convex optimization problem using Linear Matrix Inequalities (LMIs). Velocity and force transmissions in articulated multi-wheeled mobile robots are introduced into a generic form decomposed by task, joint and contact levels. A tyre-model is used for the evaluation of the robustness of the solution in relation to slippage phenomena. Simulation results show that the traction distribution forces which is so determined lead to a significant increase of obstacle clearance capacities compared to an usual velocity control technique.

Keywords: Localization, Sensor Fusion, Mapping
Abstract: Most existing approaches to indoor localization focus on using either cameras or laser scanners as the primary sensor for pose estimation. In scan matching based localization, finding scan point correspondences across scans is challenging as individual scan points lack unique attributes. In camera based localization, one has to deal with images with few or no visual features as well as scale factor ambiguities to recover absolute distances. In this paper, we develop multimodal approaches for two indoor localization problems by fusing a camera and laser scanners in order to alleviate the drawbacks of each individual modality. For our first problem we recover 3 Degrees of Freedom (DoF) of a camera-laser rig on a rolling cart in a 2D plane, by using visual odometry to facilitate scan correspondence estimation. We demonstrate this approach to result in a 0.3% loop closure error for a 60m loop around the interior corridor of a building. In our second problem, we recover 6 DoF of a human operator carrying a backpack system mounted with sensors in 3D, by merging rotation estimates from scan matching and translation estimates from visual odometry, resulting in a 1% loop closure error.

Keywords: Navigation, Mapping, Recognition
Abstract: This paper describes a new approach for building 3D geometric maps using a laser rangefinder, a stereo ca-me-ra system and a mathematical system the Conformal Geometric Algebra. The use of a known visual landmarks in the map helps to carry out a good localization of the robot.These landmarks are found using the Viola and Jones algorithm and are represented with their position in the 3D virtual map. This landmarks help in the relocalization of a robot in a previously captured environment. This machine learning technique is used for ecognition of objects in the environment.

Keywords: Mapping, Sensor Fusion, Localization
Abstract: This paper presents a novel technique to register a set of two 3D laser scans obtained from a ground robot and a wall-climbing robot which operates on the ceiling to construct a complete 3D map of the indoor environment. Traditional laser scan registration methods like the Iterative Closest Point (ICP) algorithm will not converge to a global minimum without a good initial estimate of the transformation matrix. Our technique uses an overhead camera on the wall-climbing robot to keep line of sight with the ground robot and solves the Perspective Three Point (P3P) Problem to obtain the transformation matrix between the wall-climbing robot and the ground robot, which serves as a good initial estimate for the ICP algorithm to further refine the transformation matrix. We propose a novel particle filter algorithm to identify the real pose of the wall-climbing robot out of up to four possible solutions to P3P problem using Grunert’s algorithm. The initial estimate ensures convergence of the ICP algorithm to a global minimum at all times. The simulation and experimental results indicate that the resulting composite laser map is accurate. In addition, the vision-based approach increases the efficiency by reducing the number of iterations of the ICP algorithm.

Keywords: Localization, Sensor Fusion, Field Robots
Abstract: In this paper, we propose an efficient solution to 6 degrees of freedom (6DOF) localization using Unscented Kalman filter for planetary rovers. The solution is a technique augmented the Unscented Kalman filter for accurate 6DOF localization, named Augmented Unscented Kalman Filter (AUKF). The AUKF is designed to deal with problems which occur on other planets: wheel slip, visual odometry error, and gyro drift. To solve the problems, the AUKF estimates the slippage ratio in an augmented state vector, the accuracy of the visual odometry with the number of inliers among feature points, and sensor usefulness with Gyrodometry model. Experimental results of rover runs over rough terrain are presented, the effectiveness of the AUKF and its each component is shown.

Keywords: Dexterous Manipulation, Multifingered Hands
Abstract: We address the problem of choosing adequate contact forces to ensure the stability of a multi-fingered grasp in face of external disturbances of unknown intensity. The contact forces we look for are tightening, pre-strain forces rather than active, direction-related blocking forces. We compute such tightening forces, together with blocking forces and a lower-bound approximation of an existing grasp quality measure, in only one linear programming problem. The tightening forces ensure robustness to the largest-minimum resisted disturbance wrench, but a variety of optimal contact forces may be further computed from the desired robustness by solving a quadratic programming problem.

Keywords: Dexterous Manipulation, Motion Control, Biomimetics
Abstract: Human-symbiotic humanoid robots that can perform tasks dexterously using their hands are needed in our homes, welfare facilities, and other places. To improve their task performance, we propose a motion control scheme aimed at appropriately coordinated hand and arm motions. By observing human manual tasks, we identified active body-environment contact as a kind of human manual skill and devised a motion control scheme based on it. We also analyzed the effectiveness of active body-environment contact in glass-placing and drawer-opening tasks. We validated our motion control scheme through actual tests on a prototype human-symbiotic humanoid robot.

Keywords: Dexterous Manipulation, Grasping, Manipulation Planning
Abstract: We propose a heuristic approach for a regrasp planning problem. The input with a large number of discrete contact points is considered. In this setting, traditional methods of complete solution is not available. Based on wrench space information of the input, our proposed algorithm clusters the input into groups and chooses a representative contact point from each group. A global graph structure for regrasp planning is then constructed using all force closure grasps that can be formed only by representative contact points. Also described are approaches for finding a regrasping sequence from an arbitrary grasp to a grasp in the global structure. Once such regrasping sequences are found for linking the input initial and target grasps to the global graph structure, the regrasp planning problem can be solved as a graph search. The results from preliminary experiments indicate that our method can solve many problem instances efficiently.

Keywords: Dexterous Manipulation, Computer Vision, Domestic Robots
Abstract: In this paper, we propose a strategy for a dual arm robot to pick up a specific part of clothing with one hand while holding the item of clothing with its other hand. Due to the large deformability of clothing, the handling requirements differ from those required for the handling of rigid objects. In the case of holding a specific part of clothing, large deformation leads to a large variety of positions and orientations of the target part, requiring flexibility of both visual recognition and motion control. On the other hand, since the clothing can flexibly curve over the hand, a relatively large range of suitable actions is allowed for grasping the clothing. By considering these characteristics, the following three-stage strategy is proposed. First, the state of the clothing is recognized from visual observation of the clothing using a deformable-model [1]. Then, the theoretically optimal position and orientation of the hand for handling a specific part of the clothing is calculated based on the recognition results. Finally, the position and orientation of the hand is modified by considering the executable motion range of the dual arms. Preliminary experimental results using actual observations of a humanoid robot were used to validate the effectiveness of the proposed strategy.

Keywords: Neurorobotics, Learning and Adaptive Systems, Agent-Based Systems
Abstract: We propose a model of evolutionary interaction between two robots where signs used for communication emerge through mutual adaptation. Signs used in human interaction, e.g., language, gestures and eye contact change and evolve in form and meaning through repeated use. To create flexible human-like interaction systems, it is necessary to deal with signs as a dynamic property and to construct a framework in which signs emerge from mutual adaptation by agents. Our target is multi-modal interaction using voice and motion between two robots where a voice/motion pattern is used as a sign referring to a motion/voice pattern. To enable evolutionary signs (voice and motion patterns) to be recognized and generated, we utilized a dynamics model: Multiple Timescale Recurrent Neural Network (MTRNN). To enable the robots to interpret signs, we utilized ierarchical neural networks, which transform dynamics model parameters of voice/motion into those of motion/voice. In our experiment, two robots modified their own interpretation of signs constantly through mutual adaptation in interaction where they responded to the other's voice with motion one after the other. As a result of the experiment, we found that the interaction kept evolving through the robots' repeated and alternate miscommunications and re-adaptations, and this induced the emergence of diverse new signs that depended on the robots' body dynamics through the generalization capability of MTRNN.

Keywords: Neurorobotics
Abstract: Brain Computer Interface (BCI) systems based on electroencephalography (EEG) open a new communication channel for people with severe motor disabilities, without recurring to the conventional motor output pathways. The very low signal-to-noise ratio and low spatial resolution still limits severely BCIs communication bandwidth. This paper presents the ongoing work toward the development of a BCI system for wheelchair steering. A full system based on a visual P300 oddball paradigm is proposed. The signal processing algorithms are computationally efficient and require a short phase training. Temporal features and EEG channels are selected through a Fisher criteria. For enhancement of signal-to-noise ratio and data dimensionality reduction, a spatial filter named Common Spatial Patterns is applied. This method is widely used for classification of motor imagery events, however it is not very often used for classification of event related potentials such as P300. In this paper we show that Common Spatial Patterns is an effective approach to improve P300 classification rates. In our approach, the input features for classification are the projections of the filtered data instead of the variance of the projections as typically used in motor imagery. Offline classification results, obtained with a Bayesian classifier, are presented showing the effectiveness of the overall methodology.

Keywords: Learning and Adaptive Systems, Motion Control, Entertainment Robotics
Abstract: Most of the Central Pattern Generator (CPG) models are based on defining explicit dynamical systems and finding the appropriate parameters. In this paper, we propose a novel CPG model that is based on altering a nonlinear oscillator to obtain desired limit cycle behavior. This CPG model benefits from an explicit basin of attraction and also fast convergence behavior. The presented CPG model is used in an imitation model that tries to learn the proper periodical behavior by looking at a mentor. First, a mentor performs the desired periodical behavior. Then, a hand-eye coordination process, inspired from infant babbling, is initiated to extract proper motor actions from what is observed. The extracted motor actions are finally embedded into the CPG model for smooth reproduction. This imitation model is implemented on a robotic marionette behavior learning task. The outcome of the final performance of the robotic marionette is behaviorally understandable smooth actions.

Keywords: Evolutionary Robotics, Learning and Adaptive Systems
Abstract: This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environment is available. Generally, it is widely said that this type of learning method is not appropriated to obtain dynamic motions because Markov property is not necessarily guaranteed during the dynamic task. However, in this study, we try to avoid this problem by embedding the dynamic information in the robotic state space; the applicability of the proposed method is considered using both the real robot and dynamic simulator. This paper, in particular, discusses how the robot with 5-DOF, in which the Q-Learning algorithm is implemented, acquires a giant-swing motion. Further, we describe the reward effects on the Q-Learning. Finally, this paper demonstrates that the application of the Q-Learning enable the robot to perform a very attractive giant-swing motion.

Keywords: Dynamics, Kinematics, Wheeled Robots
Abstract: Skid-steered vehicles are often used as outdoor mobile robots due to their robust mechanical structure and high maneuverability. Sliding along with rolling is inherent to general curvilinear motion, which makes both kinematic and dynamic modeling difficult. For the purpose of motion planning this paper develops and experimentally verifies dynamic models of a skid-steered wheeled vehicle for general planar (2D) motion and for linear 3D motion. These models are characterized by the coefficient of rolling resistance, the coefficient of friction, and the shear deformation modulus, which have terrain-dependent values. The dynamic models also include motor saturation and motor power limitations, which enable correct prediction of vehicle velocities when traversing hills. It is shown that the closed-loop system that results from inclusion of the dynamics of the (PID) speed controllers for each set of wheels does a much better job than the open loop model of predicting the vehicle linear and angular velocities. Hence, the closed-loop model is recommended for motion planning.

Keywords: Dynamics, Wheeled Robots, Motion Control
Abstract: A robust dynamic feedback controller is designed and implemented, based on the dynamic model of the six-wheel skid-steering RobuROC6 robot, performing high speed turns. The control inputs are respectively the linear velocity and the yaw angle. The main object of this paper is to elaborate a sliding mode controller, proved to be robust enough to ignore the knowledge of the forces within the wheel-soil interaction, in the presence of sliding phenomena and ground level fluctuations. Finally, a 3D simulation is performed with an accurate physical engine to evaluate the efficiency of this designed control law.

Keywords: Dynamics, Field Robots
Abstract: An Unmanned Ground Vehicle (UGV) capable of executing controlled sliding and sharp turns without a significant decrease in velocity would have superior utility in field operations compared to a standard UGV. Such a vehicle would be better able to maneuver in tight corridors, avoid obstacles detected at short range, and minimize its time in dangerous situations. This paper presents theoretical analysis and experimental results of a UGV executing extreme dynamic maneuvers by altering its internal mass and inertial properties during locomotion. The behaviors are accomplished by shifting the location of the UGV's center of mass while executing a turn. This modifies the normal force acting on the wheels, which in turn modifies their maximum lateral traction forces.

Keywords: Dynamics, Motion Control, Parallel Robots
Abstract: In this paper, we propose a control method to swing up and stabilize a double Furuta pendulums (DFP).The DFP is a rotational type inverted pendulum system that has a base-link and two pendulums of different length at the both ends of the base-link. The proposed method consists of three controllers for the DFP, i.e., a swinging up controller for a long pendulum, a controller to keep a long pendulum at the upright position and to swing up a short pendulum simultaneously, and a stabilization controller for both pendulums at the upright position. Since the second controller has two objectives, we use safe manual control[3] proposed by Astrom and Akesson. This paper proposes a novel application of the safe manual control. Swinging up and stabilization of the DFP was successfully achieved by appropriately switching three controllers. The effectiveness of the proposed method was verified by simulation and experiment.

Keywords: Physical Human-Robot Interaction, Manipulation and Compliant Assembly, Dynamics
Abstract: This paper proposes an object dynamics virtualization that enables a human operator to handle the object easy for a given task by changing dynamics of the object by a robot assistance. The proposed method uses a force sensor fixed between an end effector of the manipulator and an object to measure force/torque applied by the manipulator to the object. Then, force/torque applied by an operator are estimated by using a disturbance observer, which subtracts the sensing force/torque from those calculated based on the object acceleration. Using the force sensor makes implementation easier by isolating the object dynamics from those of the manipulator. By using a virtual internal model driven by the estimated force/torque, a task-oriented mechanical impedance is given to the object that is in reality heavy and unbalanced as if it were lighter and well-balanced. Experiments to virtualize dynamics of a rod with a weight at one end, i.e., an example of an unbalanced object, to be a uniform disc by a SCARA manipulator with three degrees-of-freedom were conducted, and the results showed the validity of the proposed method.

Keywords: Personal Robots, Path Planning for Manipulators, Range Sensing
Abstract: This paper presents significant steps towards the online integration of 3D perception and manipulation for personal robotics applications. We propose a modular and distributed architecture, which seamlessly integrates the creation of 3D maps for collision detection and semantic annotations, with a real-time motion replanning framework. To validate our system, we present results obtained during a comprehensive mobile manipulation scenario, which includes the fusion of the above components with a higher level executive.

Keywords: Personal Robots, Service Robots, Nonholonomic Motion Planning
Abstract: Assistive mobile robots that can navigate autonomously can greatly benefit people with mobility impairments. Since an assistive mobile robot transports a human user from one place to another, its motion should be comfortable for human users. Moreover, it should be possible for users to customize the motion according to their comfort. While there exists a large body of work on motion planning for mobile robots, very little attention has been paid to characterizing comfort and planning comfortable trajectories.

In this paper, we first characterize comfortable motion by formulating a measure of discomfort as a weighted sum of the total travel time and time integrals of various kinematic quantities. We then present a method for factoring the weights such that once a user has customized the weights for one task, the same choice of weights leads to similar average value of the discomfort measure in other tasks.

We seek trajectories that minimize the discomfort and satisfy boundary conditions on pose, velocity and acceleration. Such a problem can naturally be formulated as a variational optimization problem. Unlike previous work, we present a comprehensive formulation that allows the travel time to be unspecified and includes boundary conditions on position, orientation, velocity and acceleration. This makes the formulation very general as it can be used to compute trajectories for various kinds of tasks, such as starting from rest, coming to rest, moving from one specified velocity to another, arriving at a goal with a specified orientation etc. Finally, we present a fast and robust numerical method for solving the minimization problem.

Keywords: Personal Robots, AI Reasoning Methods, Learning and Adaptive Systems
Abstract: Knowledge processing is an essential technique for enabling autonomous robots to do the right thing to the right object in the right way. Using knowledge processing the robots can achieve more flexible and general behavior and better performance. While knowledge representation and reasoning has been a well-established research field in Artificial Intelligence for several decades, little work has been done to design and realize knowledge processing mechanisms for the use in the context of robotic control.

In this paper, we report on KnowRob, a knowledge processing system particularly designed for autonomous personal robots. KnowRob is a first-order knowledge representation based on description logics that provides specific mechanisms and tools for action-centered representation, for the automated acquisition of grounded concepts through observation and experience, for reasoning about and managing uncertainty, and for fast inference --- knowledge processing features that are particularly necessary for autonomous robot control.

Keywords: Computer Vision, Recognition
Abstract: One of the key competencies required in modern robots is finding objects in complex environments. For the last decade, significant progress in computer vision and machine learning literatures has increased the recognition performance of well localized objects. However, the performance of these techniques is still far from human performance, especially in cluttered environments. We believe that the performance gap between robots and humans is due in part to humans' use of an attention system. According to cognitive psychology, the human visual system uses two stages of visual processing to interpret visual input. The first stage is a pre-attentive process perceiving scenes fast and coarsely to select potentially interesting regions. The second stage is a more complex process analyzing the regions hypothesized in the previous stage. These two stages play an important role in enabling efficient use of the limited cognitive resources available. Inspired by this biological fact, we propose a visual attentional object categorization approach for robots that enables object recognition in real environments under a critical time limitation. We quantitatively evaluate the performance for recognition of objects in highly cluttered scenes without significant loss of detection rates across several experimental settings.

Keywords: Computer Vision, Recognition, Visual Tracking
Abstract: In the recent past, the recognition and localization of objects based on local point features has become a widely accepted and utilized method. Among the most popular features are currently the SIFT features, the more recent SURF features, and region-based features such as the MSER. For time-critical application of object recognition and localization systems operating on such features, the SIFT features are too slow (500-600 ms for images of size 640x480 on a 3 GHz CPU). The faster SURF achieve a computation time of 150-240 ms, which is still too slow for active tracking of objects or visual servoing applications. In this paper, we present a combination of the Harris corner detector and the SIFT descriptor, which computes features with a high repeatability and very good matching properties within approx. 20 ms. While just computing the SIFT descriptors for computed Harris interest points would lead to an approach that is not scale-invariant, we will show how scale-invariance can be achieved without a time-consuming scale space analysis. Furthermore, we will present results of successful application of the proposed features within our system for recognition and localization of textured objects. An extensive experimental evaluation proves the practical applicability of our approach.

Keywords: Computer Vision, Localization, Recognition
Abstract: Speed and precision are important for object detection algorithms. In this paper, a novel object detection algorithm based on color histogram and adaptive bandwidth mean shift is proposed. The algorithm is capable of detecting objects rapidly and precisely. It is composed of two stages: a rough detection stage and a precise detection stage. At the rough detection stage, histogram back projection and thresholding are applied to fast object identification and rough global localization. At the precise detection stage, the precise position, size and orientation are derived under the adaptive bandwidth mean shift framework. Experiments verify that the algorithm is able to detect the size, position and orientation of general objects rapidly and precisely.

Keywords: Computer Vision, Recognition, Domestic Robots
Abstract: We consider the problem of robotic object detection of such objects as mugs, cups, and staplers in indoor environments. While object detection has made significant progress in recent years, many current approaches involve extremely complex algorithms, and are prohibitively slow when applied to large scale robotic settings. In this paper, we describe an object detection system that is designed to scale gracefully to large data sets and leverages upward trends in computational power (as exemplified by Graphics Processing Unit (GPU) technology) and memory. We show that our GPU-based detector is up to 90 times faster than a well-optimized software version and can be easily trained on millions of examples. Using inexpensive off-the-shelf hardware, it can recognize multiple object types reliably in just a few seconds per frame.

Keywords: Computer Vision, Physical Human-Robot Interaction, Virtual Reality and Interfaces
Abstract: This paper presents a method for multi-view 3D modeling of human bodies using virtual stereopsis. The algorithm expands and improves the method used in [5], but unlike that method, our approach does not require multiple calibrated cameras and/or carefully-positioned turn tables. Instead, an algorithm using SIFT feature extraction is employed and an accurate motion estimation is performed to calculate the position of virtual cameras around the object. That is, by employing a single pair of cameras mounted on a same tripod, our algorithm computes the relative pose between camera and object and creates virtual cameras from the consecutive images in the video sequence. Besides not requiring any special setup, another advantage of our method is in the simplicity to obtain denser models if necessary: by only increasing the number of sampled images during the object-camera motion. As the quantitative results presented here demonstrate, our method compares to the PMVS method, while it makes it much simpler and cost-effective to implement.

Keywords: Visual Tracking, Recognition, Gesture, Posture, Social Spaces and Facial Expressions
Abstract: In previous work, the authors have been developing a stochastic model based approach for on-line segmentation of whole body human motion patterns during human motion observation and learning, using a simplified kinematic model of the human body. In this paper, we extend the proposed approach to larger, more realistic kinematic models, which can better represent a larger variety of human motions. These larger models may include spherical in addition to revolute joints. We examine the effects on segmentation performance due to motion representation choice, and compare the segmentation efficacy when Cartesian or joint angle data is used. The approach is tested on whole body human motion data modeled with a 42DoF kinematic model. The results indicate that Cartesian data seems to correspond most closely to the human evaluation of segment points. The experiments also demonstrate the efficacy of the segmentation approach for large kinematic models and a variety of human motions.

Keywords: Computer Vision, AI Reasoning Methods
Abstract: The ability to detect, and track multiple moving objects like person and other robots, is an important prerequisite for mobile robots working in dynamic indoor environments. We approach this problem by detecting independently moving objects in image sequence from a monocular camera mounted on a robot. We use multi-view geometric constraints to classify a pixel as moving or static. The first constraint, we use, is the epipolar constraint which requires images of static points to lie on the corresponding epipolar lines in subsequent images. In the second constraint, we use the knowledge of the robot motion to estimate a bound in the position of image pixel along the epipolar line. This is capable of detecting moving objects followed by a moving camera in the same direction, a so-called degenerate configuration where the epipolar constraint fails. To classify the moving pixels robustly, a Bayesian framework is used to assign a probability that the pixel is stationary or dynamic based on the above geometric properties and the probabilities are updated when the pixels are tracked in subsequent images. The same framework also accounts for the error in estimation of camera motion. Successful and repeatable detection and pursuit of people and other moving objects in realtime with a monocular camera mounted on the Pioneer 3DX, in a cluttered environment confirms the efficacy of the method.

Keywords: Computer Vision, Recognition, Intelligent Vehicles
Abstract: This paper presents a novel image based detection method for pedestrians at very small scales (between 16 x 20 and 32 x 40). We propose a set of new distinctive image features based on collections of local image gradients grouped by a superpixel segmentation. Features are collected and classified using AdaBoost. The positive classified features then vote for potential hypotheses that are collected using a mean shift mode estimation approach. The presented method overcomes the common limitations of a sliding window approach as well as those of standard voting approaches based on interest points. Extensive tests have been produced on a dataset with more than 20000 images showing the potential of this approach.

Keywords: Biomimetics, Biologically-Inspired Robots, Autonomous Agents
Abstract: In our previous studies, we succeeded in constructing self-oscillating gel actuator such as a self-walking gel and a dynamic motion of a gel actuator. However, the speed of the swelling-deswelling self-oscillation is too slow in order to realize practical chemical robot. In this study, we succeeded in the wide-range control of the period for the swelling-deswelling self-oscillation of a novel polymer gel by selection of the initial concentration of the Belouzov-Zhabotinsky (BZ) substrates and the temperature. The novel polymer gel was composed of a non-thermoresponsive and biocompatible poly-vinylpyrrolidone (PVP) main chain covalently-bonded to the ruthenium catalyst for the BZ reaction. Moreover, we clarified the influence of the initial concentration of the BZ substrates and the temperature on the period and the self-oscillating behavior. By optimizing the initial concentration of the BZ substrates, we cause the swelling-deswelling self-oscillation in 0.5 Hz. The maximum frequency (0.5Hz) of the novel gel was 20 times higher than for the conventional-type self-oscillating gel. Moreover, we showed that the displacement of the self-oscillation for the gel has a trade-off relationship against the period of the self-oscillation.

Keywords: Biomimetics, Biologically-Inspired Robots, Micro/Nano Robots
Abstract: In this proceeding, we introduce peristaltic gel actuators as a chemical robot. The polymer gels prepared here have a cyclic reaction network like metabolic process in itself. With a cyclic reaction, the polymer gel swells-shrinks autonomously. The periodic self-oscillating motion of the gel is produced by the dissipating chemical energy of the oscillatory Belouzov-Zhabotinsky (BZ) reaction. We have succeeded in convey the object automatically by utilizing the synthetic polymer gel. This experimental fact represents the great possibility of the chemical robot.

Keywords: Physical Human-Robot Interaction, Flexible Arms, Force Control
Abstract: The use of robots in assistive roles will be an increasingly significant application for robotics. Assistive robots need to physically interact with humans in a safe manner. We propose the use of inflatable robot links as structural members instead of traditional rigid links. We believe such links would allow the development of inherently safe robots. For these robots to be useful in tasks such as assisting humans, it is essential that we be able to control contact forces with these robots. In this paper, we propose a model for force control with a single inflatable link, investigate the dynamics of the model, and present experimental results.

Keywords: Biomimetics, Contact Modelling, Micro-manipulation
Abstract: Mechanical properties of biological cells play an important role in regulating cellular functions. Some micromanipulation methods have been reported in the literature to measure cell mechanics, but they are either high-costly or difficultly-operated. This paper presents our approach to use microrobotic cell injection technology as the test bed to characterize the mechanical properties of biological cells, by virtue of low cost and easy operation. By extending our previous work [41], we develop a mechanical model to interpret the mechanical responses during microinjection and extract the cells properties. Both finite element analysis and microinjection experiments are performed to verify the mechanical model. It is shown that the results obtained from the proposed mechanical model agree well with that obtained from finite element analysis and the experiments. Elastic moduli of zebrafish embryos at different developmental stages are characterized. This demonstrates not only the validity of the proposed model but also the fact that the microrobotic cell injection technology combining with the mechanical model can be used to characterize the mechanical properties of biological cells.

Keywords: Distributed Robot Systems, Cellular and Modular Robots, Cooperating Robots
Abstract: One of the most amazing phenomena widely observed in nature is self-assembly; living systems spontaneously form their body structure through the developmental process. While this remarkable phenomenon are not thoroughly understood in biology, the concept of self-assembly becomes undeniably indispensable also in artificial systems as they increase in size and complexity. B ased on this consideration, this paper discusses the realization of self-assembly with the use of a multi-robotic system each of which has simple motile function. The main contributions of this paper are twofold: the first concerns a fully decentralized control method derived from the mutual entrainment between coupled nonlinear oscillators; and the second is related to the exploitation of physical interaction between agents stemming from a passive deformation mechanism, which allows an efficient movement of individual agents during the course of self-assembly. Here, form generation by self-assembly is considered as the result of time evolution toward the most dynamically stable state. Owing to this, in principle, the proposed method also satisfies significant ability of self-repair without making any modification to the proposed algorithm. In this paper we validate proposed method by exploiting real physical robotic agents. Experimental results show that stable and spontaneous self-assembly is achieved irrespective of the initial positional relationship between the agents.

Keywords: Distributed Robot Systems, Behaviour-Based Systems, Biologically-Inspired Robots
Abstract: We study a simple algorithm inspired by the Brazil nut effect for achieving segregation in a swarm of mobile robots. The algorithm lets each robot mimic a particle of a certain size and broadcast this information locally. The motion of each particle is controlled by three reactive behaviors: random walk, taxis, and repulsion by other particles. The segregation task requires the swarm to self-organize into a spatial arrangement in which the robots are ranked by particle size (e.g., annular structures or stripes).

Using a physics-based computer simulation, we study the segregation performance of swarms of 50 mobile robots. The robots represent particles of three different sizes. We first analyze the problem of how to combine the basic behaviors so as to minimize the percentage of errors in rank. We then show that the system is very robust to noise on inter-robot perception and communication. For a noise level of 50%, the mean percentage of errors in rank is 1%. Moreover, we investigate a simplified version of the control algorithm, which does not rely on communication.

Finally, we show that the mean percentage of errors in rank decreases exponentially as the particles' size ratio increases. As the error is bounded, one can achieve 100% error-free segregation. The reduction in error, however, comes at the expense of an increase in the required sensing/communication range.

Keywords: Distributed Robot Systems, Networked Robots, Sensor Networks
Abstract: This paper presents practical design and hardware implementation issues of self-configuring swarms of autonomous mobile robots. For the purpose, we develop a new low-cost position detection system that we call dual rotating infrared (DRIr) sensor. The DRIr sensor provides robots with advanced sensing capabilities that give reliable information about the position and surface geometry of neighboring robots and obstacles. Special focus is placed on how to realize the observation function of robots through the use of DRIr sensors. We verify the functionality and performance of the DRIr sensors mounted on the mobile robots. Experimental results show that a swarm of mobile robots equipped with the DRIr sensors can autonomously configure themselves into an area.

Keywords: Distributed Robot Systems, Cooperating Robots, Adaptive Control
Abstract: This paper presents a novel method for shape control of a swarm of robots based on region control concept. Multiplicative potential energy function is used to form the overall desired shape of the entire swarm. The shape formed using this method is a union of all the regions defined by corresponding inequality functions. This proposed method is a complement to our previous method where the additive potential energy is used to form the desired shape. By combining the multiplicative and additive potential energies, a variety of complicated shapes can be formed. Lyapunov-like function is presented for convergence analysis of the multi-robot systems. Simulation results are presented to illustrate the performance of the proposed method.

Keywords: Range Sensing, Mapping, Wheeled Robots
Abstract: This paper presents a low-cost, simple automated mobile platform for 3D environmental digitization. Compared with previous 3D digitization platforms, our platform does not need servo motors to rotate the 2D LRF sensor. In order to build a 3D model of a salient target, we present a new viewpoint planning method for fast registration of 3D shape. Within a predefined accuracy, our method can determine the minimum overlap between two consecutive scanning images to speed up the digitization process. This guarantees the next scanning image can be merged to the previous one properly. The results from both simulation and experiments show the effectiveness of our viewpoint planning method. Our tests of this mobile robot system demonstrate the feasibility of 3D digitization based on a low-cost platform.

Keywords: Localization, Navigation, Mapping
Abstract: Olfaction is a long distance sense, which is widely used by animals for foraging or reproductive activities. Olfaction plays a significant role in natural life of most animals. For some animals, olfactory cues are far more effective than visual or auditory cues in search for objects such as foods and nests. Although chemical sensing is far simpler than vision or hearing, navigation in a chemical diffusion field is still not well understood. Therefore, this powerful primary sense has rarely been used inside the robotics community. This paper presents an effective olfactory-based planning and search algorithms for using on mobile robots. Olfactory-based robots use odors as a guide to navigate and track in the unknown environments. The planning algorithms are based on Bayesian inference theory and artificial potential field methods. Inputs to the algorithms include the measured flow and the detection or non-detection events that happened at the robot location. This methodology results in algorithms for predicting likelihood of source location versus position. The robot would then optimize a desired trajectory to navigate in the odor plume and locate the odor source location.

Keywords: Path Planning for Manipulators, Range Sensing, Computer Vision
Abstract:

Keywords: Navigation, Robotics in Hazardous Fields, Behaviour-Based Systems
Abstract: A large-scale navigation system for autonomous off-road robots is presented which uses a topological map to navigate to a previously unseen target location. During path traversal, the system relies on a local navigation layer to avoid obstacles not modeled in the map. Data from this local layer is abstracted to learn both realistic topological edge cost measures and local traversability maps which allow more efficient route selection during topological exploration. On the topological level, a technique to handle impassable route segments in the map is presented and an exploration strategy that allows to discover new routes to the goal is introduced. The performance of the proposed concept is experimentally validated on the robot RAVON at the 2nd Military European Land Robot Trial 2008.

Keywords: Navigation
Abstract: Robotic obstacle avoidance in cluttered and dense environments is an important issue in robotic navigation. Over the past few years a number of techniques has been proposed to deal with safe navigation among obstacles in unknown scenarios. Unfortunately many of these methods do not consider obstacle velocities, which can rise some serious questions concerning their safety. This paper will deal with a novel approach to moving obstacle avoidance in holonomic robots. It proposes the Forbidden Velocity Map, a generalization of the Dynamic Window concept that considers obstacle and robot shape, velocity and dynamics, resulting in a safe, reactive real-time navigation algorithm that is able to deal with navigation in unpredictable and cluttered scenarios.

Keywords: Navigation, Intelligent Vehicles, Field Robots
Abstract: This paper proposes an adaptive node sampling method for the probabilistic roadmap (PRM) planner. The proposed method substitutes the random sampling in the learning phase of the PRM planner and improves the connectivity of the roadmap. This method uses two phase to determine nodes in order to construct the roadmap. First, the proposed method extracts initial nodes using the approximated cell decomposition and the Harris corner detector. Second, the positions of these nodes are optimized using a construction process of the centroidal voronoi tessellation (CVT). The proposed method determines the adequate number and positions of the nodes to represent the entire free spaces, and the PRM planner based on the proposed method finds out efficient paths even in narrow passages. These properties have been verified though experiments.

Keywords: Navigation, Field Robots, Mapping
Abstract: Algorithms such as Field-D* produce continuous fields of costdistance-to-goal, where costdistance is cost integrated over distance. Field values have traditionally been used as direct input to trajectory planners. In contrast, we focus on the the problem of extracting a minimum costdistance path between two locations, given the continuous field. We identify a suboptimal phenomenon that occurs when standard path extraction techniques are used on linearly interpolated quantity-to-goal fields (the particular type of continuous field created with algorithms like Field-D*). The phenomenon causes paths to drift sideways toward their horizontal or vertical bounds, resulting in increased path length and unnecessary turns. We mathematically explain the cause of this suboptimality, and demonstrate that it is a consequence of the linear interpolation used to create the costdistance-to-goal field. We present an improvement that calculates path segment directions using an interpolation between the costdistance-to goal gradient vectors at neighboring nodes, and perform a series of experiments comparing this method with the current state-of-the-art. We find that gradient interpolation techniques can achieve a significant reduction in path length error, and we provide discussion and examples of when they should and should not be used.

Keywords: Navigation, Robotics in Hazardous Fields
Abstract: We propose an efficient method for updating a path that was computed using level-set methods. Our approach is suitable for autonomous vehicles navigating in a static environment for which an a priori map of the environment is inaccurate. When the autonomous vehicle detects a new obstacle, our algorithm replans an optimal route without recomputing the entire path. Computational costs when planning paths with level set methods are due to creation of the level set. Once the level set has been computed, the optimal path is simply gradient descent down the level set. Our approach is based on formal analysis of how the level set changes when a new obstacle is detected. We show that in many practical cases, only a small portion of the level set needs to be re-computed when a new obstacle is detected. Simulation examples are presented to validate the effectiveness of the proposed method.

Keywords: Marine Robotics, Autonomous Agents, Intelligent Vehicles
Abstract: In order to improve the efficiency of a terrain covering algorithm for a robot(AUV), an artificial island(AI) technique is developed. Such an algorithm is necessary to acquire information and make a terrain map in an unknown three dimensional underwater environment. This algorithm considers that the three dimensional environment consists of a number of planes, at various ocean depths. The artificial island technique has the advantage of reducing the covering path length and the time cost for the robot, because it takes the correlation between every plane. In this paper, the concept of the artificial island technique is presented and its validity is proved under certain conditions. Through various simulations, we validate the efficiency in terms of the total path length and the running time of the AUV. An example of a complete three dimensional map obtained using this technique is provided.

Keywords: Marine Robotics, SLAM, Localization
Abstract: Our aim is to explore the fundamental stability issues of a robotic vehicle carrying out localization, mapping, and feedback control in a perturbation-filled environment. Motivated by the application of an ocean vehicle performing an autonomous ship hull inspection, our planar vehicle model performs localization using point features from a given map. Cases in which the agent must update the map are also considered. The stability of the controller and estimator duo is investigated using a pair of theorems requiring boundedness and convergence of the transition matrix Euclidean norm. These theorems yield a stability test for the feedback controller. Perturbations are then considered using a theorem on the convergence on the perturbed system transition matrix, yielding a robustness test for the estimator. Together, these tests form a set of tools which can be used in planning and evaluating the robustness of marine vehicle survey trajectories, which is demonstrated through experiment.

Keywords: Marine Robotics, Autonomous Agents, Intelligent Vehicles
Abstract: Autonomous underwater vehicles (AUVs) are an indispensable tool for marine scientists to study the world's oceans. The Slocum glider is a buoyancy driven AUV designed for missions that can last weeks or even months. Although successful, its hardware and layered control architecture is rather limited and difficult to program. Due to limits in its hardware and software infrastructure, the Slocum glider is not able to change its behavior based on sensor readings while underwater. In this paper, we discuss a new programming architecture for AUVs like the Slocum. We present a new model that allows marine scientists to express AUV missions at a higher level of abstraction, leaving low-level software and hardware details to the compiler and runtime system. The Slocum glider is used as an illustration of how our programming architecture can be implemented within an existing system. The Slocum's new framework consists of an event driven, finite state machine model, a corresponding compiler and runtime system, and a hardware platform that interacts with the glider's existing hardware infrastructure. The new programming architecture is able to implement changes in glider behavior in response to sensor readings while submerged. This crucial capability will enable advanced glider behaviors such as underwater communication and swarming. Experimental results based on simulation and actual glider deployments off the coast of New Jersey show the expressiveness and effectiveness of our prototype implementation.

Keywords: Marine Robotics, Control Architectures and Programming
Abstract: This paper presents the design and implementation of a Mission Control System (MCS) for an Autonomous Underwater Vehicle (AUV) based on Petri nets. In the proposed approach the Petri nets are used to specify as well as to execute the desired autonomous vehicle mission. The mission is easily described using an imperative programming language called Mission Control Language (MCL) that formally describes the mission execution thread. A Mission Control Language Compiler (MCL-C) able to automatically translate the MCL into a Petri net is described and a real-time Petri net player that allows to execute the resulting Petri net onboard an AUV are also presented.

Keywords: Humanoid Robots, Dynamics, Motion Control
Abstract: This paper describes 3D biped walking generation and control based on Limit Cycle Walking. In our study, we use the simplest possible 3D biped model with three DOFs, incorporating roll and pitch motions in the frontal/sagittal planes, respectively. Our approach dynamically decouples these two motions, stabilizes pitch motion in the sagittal plane via the Limit Cycle Walking approach, introduces robustness for this motion using energy feedback control, and robustness for roll motion based on reference trajectory feedback tracking control. The roll reference trajectory is generated via analysis of the impact dynamics. Performance is verified via simulations.

Keywords: Humanoid Robots, Biologically-Inspired Robots, Legged Robots
Abstract: We present a novel method of guiding a humanoid robot, including stepping, by allowing a user to move its head. The motivation behind this approach comes from research in the field of human neuroscience. In human locomotion it has been found that the head plays a very important role in guiding and planning motion. We use this idea to generate humanoid whole-body motion derived purely as a result of moving the head joint. The input to move the head joint is provided by a user via a 6D mouse. The algorithm presented in this study judges when further head movement leads to instability, and then generates stepping motions to stabilize the robot. By providing the software with autonomy to decide when and where to step, the user is allowed to simply steer the robot head (via visual feedback) without worrying about stability. We illustrate our results by presenting experiments conducted in simulation, as well as on our robot, HRP2.

Keywords: Neurorobotics, Humanoid Robots, Animation and Simulation
Abstract: Fluid bipedal locomotion remains a significant challenge for humanoid robotics. Recent bio-inspired approaches have made significant progress by using small numbers of tightly coupled neurons, called central pattern generators (CPGs). Our approach exchanges complexity of the neuron model for complexity of the network, gradually building a network of simple neurons capable of complex behaviors. We show this approach generates controllers de novo that are able to control 3D bipedal locomotion up to 10 meters. This results holds for robots with human-proportionate morphologies across 95% of normal human variation. The resulting networks are then examined to discover neural structures that arise unusually often, lending some insight into the workings of otherwise opaque controllers.

Keywords: Humanoid Robots, Biologically-Inspired Robots, Legged Robots
Abstract: This paper discusses the mechanical kinematics solutions and design aspects of the biped robot SHERPA, a bipedal platform able to walk and carry load. Starting from the analysis of the human lower limbs, we figure out that 6 DOF per leg are fundamental for a correct walking motion and can be adopted in a mechanical design of a humanoid robot. A close investigation of the joints leads us to a novel modular mechanical design, with a parallel architecture mechanism characterized by and high degree of interchangeable components. The robot is using twelve high performance hollow shaft electrical actuators acting in pairs in a parallel manner, a remote compact and transparent actuation with zero-backlash cable transmissions, 2 DOF differential joints between each segment of the limb and a light-weight carbon fiber skeleton modeling and mimic the anatomy of the human legs. The modular 2 DOF cable differential joint has been successfully implemented at the hip, knee and ankle level. Using our approach, actuation is more transparent (backdrivable, with low inertia) and will allows SHERPA to interact with the environment more smoothly which leads to better walking ability.

Keywords: Legged Robots, Dynamics, Humanoid Robots
Abstract: The planar compass-gait biped has been extensively studied in the dynamic walking community, motivated by the gravity-based pendular efficiencies of human walking. These results can be extended to three dimensions using controlled geometric reduction for open-chain robots, by which stable 3-D walking gaits are built from known sagittal-plane limit cycles. We apply this method to the standard and with-torso compass-gait (hipless) bipeds, showing straight-ahead walking gaits (i.e., stable 1-step periodic limit cycles) as well as h-step turning in full circles (i.e., stable h-periodic limit cycles). These constant-curvature maneuvers are composed of stable 1-periodic turning gaits modulo heading change, demonstrating two types of gaits for directional dynamic walking in three dimensions.

Keywords: Rehabilitation Robotics, Neural and Fuzzy Control, Motion Control
Abstract: This work deals with neural network-based gait-pattern adaptation algorithms for an active lower limbs orthosis. Stable trajectories are generated during the optimization process, considering a stable trajectory generator based on the Zero Moment Point criterion and the inverse dynamic model. Additionally, two neural network (NN) are used to decrease the time-consuming computation of the model and ZMP optimization. The first neural network approximates the inverse dynamics and the ZMP optimization, while the second one works in the optimization procedure, giving the adapting parameter according to orthosis-patient interaction. Also, a robust controller based on the H-infinity method is designed to attenuate the effects of external disturbances and parametric uncertainties in the trajectory tracking errors. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results.

Keywords: Rehabilitation Robotics, Human Performance Augmentation, Physical Human-Robot Interaction
Abstract: This paper introduces a cooperative control algorithm that designs a stable biped walk satisfying a wearer's intention relating to his/her walk such as a timing to start and stop walking, walking speed and waking direction so on, so that an exoskeletal walking support system could provide a comfortable support to a paraplegia patient. At first, a pair of gloves with several DOFs is developed to convey a wearer's intention to the walking support system. He/she swings both his/her index fingers to simulate foot motions of his/her walking. The amplitude and period of the swing corresponds to a step length and period of the walk, respectively. Pronation/supination of the wrist joint of his/her right arm corresponds to a walk direction. The cooperative control algorithm based on a cart-table model designs trajectories of each joint for stable walking pattern that satisfies the intention expressed by the wearer's hand motion and then the designed walking pattern is executed in realtime by the walking support system. As the first trial, a small humanoid robot ``HRP-2m" is used for safety as a control target that will be a combination of a wearer and the walking support system in the final situation. Through some experiments we confirm that our proposed algorithm enables the humanoid robot to start and stop stable walk with variable step length in the desired walking direction according to operator's intentions.

Keywords: Rehabilitation Robotics
Abstract: This paper proposes a robotic walker system with standing, walking and seating assistance function. Our system focuses on domestic use for aged person who needs nursing in their daily life. Our key ideas are two topics. The first topic is combination of standing assistance function and walking assistance function. In previous works, many assistance devices are specialized in only "standing-up operation" or "walking operation". However, in their daily life, elderly people need standing, walking and seating assistance continuously by the same device. Therefore, our developing assistance system can support both operations by a small sized mechanism which is easy to use in the home. The second topic is a seating position adjustment assistance. From questionnaires of nursing specialists, a seating position adjustment requires the elderly people to walk backward and it is difficult operation for them. Furthermore, in many cases, a failure of this operation causes a fracture which has high risk to fall into bedridden life. Thus, our developing system can assist the aged users to adjust the seating position safety. The performance of our proposed system is verified by experiments using our prototype.

Keywords: Motion Control, Personal Robots, Wheeled Robots
Abstract: This paper presents a novel compliant motion controller design for an Omni-directional mobile robot. In this design, an external force observer is developed based on measuring motor current and speed without using an expensive force/torque sensor. The mobile robot has a handrail to assist the elderly to walk safely and stably. In this application, adaptive motion compliance is required in accordance with the applied force of the user. Practical experimental results show that the compliance of the walking helper can be adjusted by setting dynamic coefficients of the overall dynamical system. It was demonstrated that the external force observer successfully detected the pushing as well as pulling force of a user on the handrail. The velocity of the omni-directional walking helper is adjusted according to the inferred motion intent.

Keywords: Rehabilitation Robotics, Humanoid Robots
Abstract: When analyzed in the tangential speed domain, human movements exhibit a multi-peaked speed profile which is commonly interpreted as evidence for submovements. At slow speeds, the number of the peaks increases and the peaks also become more distinct, corresponding to non-smoothness or intermittency in the movement. In this study, we evaluate two potential sources proposed in the literature for the origins of movement intermittency and conclude that intermittency is more likely due to noise in the neuromuscular system as opposed to a central movement planner that generates intermittent plans. This conclusion is based on the assumption that the central planner would be expected to introduce similar levels of intermittency for different joints, while accumulating noise in the neuromuscular circuitry would be expected to exhibit itself as increase in noise in distal direction. We have used a 3D motion capture system to record trajectories of fingertip, wrist, elbow and shoulder as five participants completed a simple manual circular tracking task at various constant speed levels. Statistical analyses indicated that movement intermittency, quantified by a number of peaks metric, increased in distal direction, supporting the noise model for origins of intermittency. Movement speed was determined to have a significant effect on intermittency, while orientation of the task plane showed no significance.

Keywords: Medical Robots and Systems, Mechanism Design
Abstract: This paper presents the modeling of a new mini-invasive neurosurgical resection robot. This robot aims to help to remove brain tumors and is incorporated into a multi-robot neurosurgical system. We focus especially on the resection task. The robot is composed of three serial bending modules actuated by wires (cables) and uses an additional translation. The redundancy of the robot (seven degrees of freedom) allows more dexterity for the resection task. A kinematic (geometric) model is built distinguishing the structure and the actuation models, and integrating the influence of the wires into the kinematic behaviour of the robot. A method for kinematic redundancy handling is defined and assigns different parts of the robot to different tasks. An interactive path planning based on arbitrary sequence of elementary procedures assembled by the neurosurgeon is proposed and the yielding procedures are computed from the kinematic model.

Keywords: Medical Robots and Systems
Abstract: The non-invasive ultrasound theragnostic system, we propose, tracks and follows movement in an affected area —kidney stones here—, while High-Intensity Focused Ultrasound (HIFU) is irradiated onto the area. In this paper, the concept of the novel medical support system, which integrates the therapy and diagnostics, is illustrated at first. Secondly, structuring the required functions for the proposed system is discussed. Third, the overview of the constructed system configuration is illustrated. Fourth, the problem of the stone motion tracking by ultrasonography is clarified. To cope with this problem, the respiratory motion of a human kidney is analyzed and a controller, by utilizing the quasi-periodical motion of the respiratory kidney motion, is proposed. Finally, the result of the servoing and HIFU irradiation experiments of the model stone, which moves based on the real human kidney motion data, is reported to confirm the effectiveness of the proposed controller and the constructed system.

Keywords: Medical Robots and Systems, Nonholonomic Motion Planning
Abstract: Accurate insertion of needles to targets in 3D anatomy is required for numerous medical procedures. To reduce patient trauma, a "fireworks" needle insertion approach can be used in which multiple needles are inserted from a single small region on the patient’s skin to multiple targets in the tissue. In this paper, we explore motion planning for "fireworks" needle insertion in 3D environments by developing an algorithm based on Rapidly-exploring Random Trees (RRTs). Given a set of targets, we propose an algorithm to quickly explore the configuration space by building a forest of RRTs and to find feasible plans for multiple steerable needles from a single entry region. We present two path selection algorithms with different optimality considerations to optimize the final plan among all feasible outputs. Finally, we demonstrate the performance of the proposed algorithm with a simulation based on a prostate cancer treatment environment.

Keywords: Medical Robots and Systems, Micro/Nano Robots, Localization
Abstract: Future retinal therapies will be partially automated in order to increase the surgeons’ ability to operate near the sensitive structure of the human eye retina. Untethered robotic devices that achieve the desired precision have been proposed, but require localization information for their control. Since the interior of the human eye is externally observable, vision can be used for localization. Previously, a focus-based paraxial localization algorithm using a Mechatronic Vitreoretinal Ophthalmoscope (MVO) was proposed and evaluated by the authors. In this paper, the first algorithm for wide-angle intraocular localization is presented. The effectiveness of this new localization approach is demonstrated by experiments using a model eye and a customized MVO, and there is clear improvement over previously reported results.

Keywords: Medical Robots and Systems, Mechanism Design
Abstract: This paper outlines the design of a portable manipulator system for use in remote detection and care of hemorrhage using High Intensity Focused Ultrasound (HIFU). We have developed a kinematically redundant manipulator that uses high fidelity force control for safe interaction with human patients. The manipulator is outfitted with a dual imaging and sonication end-effector for hemorrhage detection and treatment. Unlike most available force controlled manipulators, the design presented in this paper has all the actuation embedded inside its body eliminating the need for a base which greatly improves portability. We review the main design features, advantages, and trade-offs of this approach and present experimental data of hemorrhage detection and controlled sonication of biological tissue samples.

Keywords: Cooperating Robots, Mechanism Design, Wheeled Robots
Abstract: We proposed new arm-wheel hybrid robot “Souki-II” which consists of a body, a pair of large bore wheels which sandwich the body and rotates around the same axis from the body, articulated hand attached to the body, and free caster attached around the wrist of the hand. Souki-II showed high terrain adaptive motion by using the large bore wheels and free caster of the hand. We also showed that the mobility can be enhanced when multiple units are connected together. Souki-II can also take the mode of a manipulator. For the joint mechanism of the Souki-II, we introduced a unit actuator system and a cover member with spiral groove to pass the electric harness and to assist in heat dissipation. From the experiments of the constructed models, we could demonstrate the innovative performance of the proposed Souki-II system.

Keywords: Wheeled Robots, Intelligent Vehicles, Search and Rescue Robots
Abstract: In this paper, we propose a control algorithm for stabilizing of an unmanned bicycle at zero speed by using a nonlinear control based on an output-zeroing controller. The simplified model of the bicycle with the balancer is derived from Lagrangian and nonholonomic constraints with respect to translation and rotation relative to the ground plane. We derived a controller using a steering torque and a balancer torque to stabilize the bicycle at zero linear velocity. The outputzeroing controller is designed by using the angular momentum of two-link system and by adding the effect of steering angle to the derivative of the angular momentum. Numerical simulation and experimental results are shown to verify the effectiveness of the proposed control strategy.

Keywords: Wheeled Robots, Distributed Robot Systems, Intelligent Vehicles
Abstract: This paper addresses the problem of coordinated path following of multiple wheeled mobile robots while keeping a desired formation. The control laws proposed are categorized into two envelopes, one is steering individual robots to trace along predefined paths, and the other is ensuring tracked paths to be well defined in the formation, by means of decentralized speed adaption.Within this framework, geometric paths following are built on Lyapunov theory and backstepping techniques, while injecting helmsman like behavior into individual path following control. Speed adaption with minimum communication variable under the constraints of multi-robot communication topology, is elaborately designed without relative speeds between neighboring robots requested. The simple but effective controller design, enables multi-robot system to be coordinated and stabilized into an invariant manifold, and all speeds converge to desired profiles in addition. Simulation results illustrate the efficacy of solution proposed.

Keywords: Wheeled Robots, Service Robots, Field Robots
Abstract: We are developing a human-riding wheeled inverted pendulum for use as a personal vehicle. To be practically usable, the vehicle requires a function that enables the rider to get on and off both safely and smoothly while on a slope of unknown angle. Concretely, for the convenience of the rider, the vehicle needs to be stabilized on an unknown slope without the rider aboard, both before the rider gets on it and after he/she gets off it. Moreover, the vehicle should be stabilized safely relative to the rider's handling force at a grip of the vehicle while getting on and off. We thus investigated a method of estimating the handling force and the slope angle separately. In this paper, we report on the construction of our system to estimate the handling force and the slope angle using a disturbance observer. We verified the validity of our proposed estimation method by computer simulations and experiments using a real prototype of a human-riding wheeled inverted pendulum vehicle on an unknown slope.

Keywords: Distributed Robot Systems, Wheeled Robots, Search and Rescue Robots
Abstract: The forward moving target segmentation from a moving platform with a pinhole camera is an important and relatively unexplored problem in visual tracking. This paper proposes a novel segmentation algorithm for extracting a moving target when using a moving platform (that follows a similar trajectory and has a camera that is not calibrated for the particular scene). When the target has unpredictable movements, we are unable to model it and the pertinent backgrounds are very different. We introduce a new entropy-based clustering algorithm in order to find a bounding box representing the target. A target model based on graph representation is also used for selecting clusters representing the moving target. To demonstrate the robust target segmentation scheme, we apply the method to a team of miniature robots (the Explorers developed at the University of Minnesota) in real tracking missions.

Keywords: Navigation, Computer Vision
Abstract: Time to Contact (TTC) has long been known as a biologically inspired method for obstacle detection and reactive control of motion that does not require scene reconstruction or 3D depth estimation. Unfortunately, time to contact does require a stable and reliable estimate of the rate of change of distance between image features. In this paper we propose a new method to measure time to contact, Active Contour Affine Scale (ACAS), and experimentally and analytically compare this with two other recently proposed methods: Scale Invariant Ridge Segments (SIRS), and Image Brightness Derivative (IBD). Our results show that ACAS provides more accurate estimation of TTC when the image flow may be approximated by an affine transformation, while IBD systematically over estimate time to contact, and SIRS provides an estimate that is generally valid, but may not always be as accurate as ACAS.

Keywords: Navigation, Autonomous Agents
Abstract: A navigation algorithm for mobile robots in unknown rough terrain has been developed. The algorithm is solely based on stereo images and suitable for wheeled and legged robots. The navigation system is able to guide the robot along a short and safe path to a goal specified by the operator and given in coordinates relative to the starting point of the robot. The algorithm uses visual odometry for localization. The terrain is modeled from stereo images and its traversability is estimated. A D* Lite planner is used for efficiently planning a short and safe path by incorporating terrain traversability in the planning process. The robot actively explores its environment as it follows the path to the goal. The algorithm has been tested on a wheel driven mobile robot and on a six-legged walking robot on rough terrain.

Keywords: Cooperating Robots, Navigation
Abstract: This paper addresses a flexible cooperative navigation system for small robot teams. The members of these groups move in formation, but with enough flexibility to be able to avoid obstacles and adapt to the environment shape. This approach is based on an analysis of the environment on a grid-based model that permits each robot to continuously evaluate the situation in which it is, in order to decide the best of the three developed navigation strategies, one for each situation type. Moreover, by using this model the robot cooperation for a coordinate navigation is improved, allowing each robot to share the observations with the other robots. So the field of view of each robot of the team on which it makes the decisions is enlarged. The system is implemented in a decentralized way so the number of robots is not a main issue, thus being scalable. Eventually, initial formation topology can be modified, in order to comply with the environment while the mission is accomplished. The system and the strategies are evaluated by means of simulations, showing the robustness against possible blocking situations.

Keywords: Computer Vision, Navigation
Abstract: Ground plane detection plays an important role in stereo vision based obstacle detection methods. In the recent past, the V-Disparity image has been widely used for ground plane detection. The existing approach based on V-Disparity image can detect flat ground successfully but have difficulty in detecting non-flat ground. For the purpose of definition, ``non-flat'' is defined as a ground surface that cannot be represented by a single planar surface. In this paper, we discuss the representation of non-flat ground in V-Disparity image, based on which a method is proposed to identify non-flat surfaces separately from obstacles. The method provides a means of properly classifying surfaces curving upwards as drivable surfaces rather than obstacles.

Keywords: Navigation, Localization
Abstract: Cameras are popular sensors for robot navigation tasks such as localization as they are inexpensive, lightweight, and provide rich data. However, fast movements of a mobile robot typically reduce the performance of vision-based localization systems due to motion blur. In this paper, we present a reinforcement learning approach to choose appropriate velocity profiles for vision-based navigation. The learned policy minimizes the time to reach the destination and implicitly takes the impact of motion blur on observations into account. To reduce the size of the resulting policies, which is desirable in the context of memory-constrained systems, we compress the learned policy via a clustering approach. Extensive simulated and real-world experiments demonstrate that our learned policy significantly outperforms any policy that uses a constant velocity. We furthermore show, that our policy is applicable to different environments. Additional experiments demonstrate that our compressed policies do not result in a performance loss compared to the originally learned policy.

Keywords: Networked Teleoperation, Telerobotics, Networked Robots
Abstract: Any teleoperation system involving two distant devices is affected by communication delay due to the physical gap between the devices. Several approaches based on wave variables have already been proposed to deal with time-varying delay. However, these approaches are too conservative resulting in high degradation from the constant time delay case. In this paper, we propose a new control scheme for bilateral teleoperation under time-varying communication delay entirely developed in the wave variables domain. The proposed method minimizes the performance degradation from the constant time delay case. Experimental results show the validity of the proposed scheme.

Keywords: Telerobotics, Haptics and Haptic Interfaces, Force and Tactile Sensing
Abstract: This paper describes a new methodology for designing bilateral controllers based on transparency that applies a modified scheme of control by state of convergence. The design is based on modelling the behavior of the master and slave which regard state space equations, and also taking into account that perfect transparency cannot be reached. This methodology allows designing the controllers in order to obtain the convergence between the state of the master and the slave. Furthermore, it consequently provides a higher degree of transparency to the operator. The paper explains criteria in achieving convergence between the master and the slave, and so as with transparency on a steady state. A set of equations that calculate controller gains have been obtained by applying such criteria. In order to verify this new methodology, a master-slave system of 3 DoF have been used.

Keywords: Telerobotics, Force and Tactile Sensing, Networked Robots
Abstract: Among the still existing issues in bilateral teleoperation, there is the inability by force-feedback control schemes to guarantee delay-independent stability and achieve both position coordination and force reflection independently of the remote environmental dynamics. Particularly, most bilateral control frameworks fail to address position coordination when interacting with rigid environments. In this paper we present a novel control strategy that aims to passively compensate for position errors that arise during contact tasks and, in general, achieve stability and transparency when alternating between unobstructed (free) and obstructed (contact) environments. The proposed control framework exploits the wave impedance independent passivity property of the scattering transformation to guarantee stability and transparency by gradually switching between a low wave impedance, ideal for free motion, and a sufficiently large impedance, suitable for contact tasks. The validity of the control framework is verified through simulations and experiments on a pair of nonlinear robots.

Keywords: Telerobotics
Abstract: Communication time delay has been a major barrier to achieving high performance while maintaining stability in bilateral teleoperation. Building upon the results of our recent work, a provably stable adaptive controller is proposed for variable delay teleoperation. The controller utilizes a model of the system dynamics and the time delay within a predictive control framework to improve the response transparency. It can also adapt to uncertainties in the user and environment dynamics. The performance objectives are delay-free position tracking between the master and slave and the establishment of a virtual mass-damper tool impedance between the user and environment. Delay reduction is accomplished based on a state observer and estimates of the system parameters. Using the delay reduced dynamics, an adaptive output regulation problem is formulated and solved. A Lypunov-based analysis of the performance and stability of the resulting system is presented. Simulation results with a single-axis teleoperation setup demonstrate the effectiveness of the proposed approach.

Keywords: Telerobotics, Physical Human-Robot Interaction
Abstract: This paper derives analytic guidelines to tune the popular Position-Force bilateral controller and improve its performance by incorporating available knowledge on the bounds of the environment impedance. The proposed guidelines can prove especially useful in the domain of telesurgery where a need exists for well-understood bilateral teleoperation controllers, that show good performance and where many tasks can be characterized by restricted and relatively easily definable impedance regions. This paper firstly analyses the two-port passivity and absolute stability properties of two alternatives of the Position-Force controller. The limitations on achievable performance when guaranteeing absolute stability with arbitrary environments are detailed. Next, a novel method, called Bounded Environment Passivity method is introduced. This method enables the design of teleoperation controllers that show passive behaviour for interactions with an environment that varies over a given range of impedances. A set of guidelines that allow a smarter trade-off between performance and stability follows. The theoretical results are verified experimentally on a 1-d.o.f. teleoperation setup.

Keywords: Learning and Adaptive Systems, Kinematics, Dynamics
Abstract: Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently change between contexts. In this paper, we present a novel approach for learning (unconstrained) control policies from movement data, where observations are recorded under different constraint settings. Our approach seamlessly integrates unconstrained and constrained observations by performing dual optimisation of two risk functionals. The first is a novel risk functional that makes a meaningful comparison between the estimated policy and constrained observations. The second is the standard risk, used to tighten the expected error bounds under impoverished sets of constraints. We demonstrate our approach on systems of varying complexity, including human motion capture data.

Keywords: Learning and Adaptive Systems, Path Planning for Multiple Mobile Robot Systems, Field Robots
Abstract: Many sensing applications require monitoring phenomena with complex spatio-temporal dynamics spread over large spatial domains. Efficient monitoring of such phenomena would require an impractically large number of static sensors; therefore, actuated sensing - mobile robots carrying sensors - is required. Path planning for these robots, i.e., deciding on a subset of locations to observe, is critical for high fidelity monitoring of expansive areas with complex dynamics. We propose MUST - a MUltiscale approach with STochastic modeling. MUST is a hierarchical approach that models the phenomena as a stochastic Gaussian Process that is exploited to select a near-optimal subset of observation locations. We discuss in detail our proposed algorithm for the important application of monitoring light intensity in a forest understory. We performed extensive empirical evaluations both in simulation using field data and on an actual cabled robotic system to validate the effectiveness of our proposed algorithm.

Keywords: Domestic Robots, Robot Companions and Social Robots in Home Environments, Medical Robots and Systems
Abstract: This paper presents a novel structure learning algorithm for the creation of distributed Bayesian networks over multiple, static and mobile processing units which compose an assistive, intelligent environment for activity recognition. We provide results demonstrating a higher level of accuracy in the recognition of fine motor tasks when the environment is augmented with a mobile robot and show the ability of our learning algorithm to reduce communication overhead when compared to standard structure learning techniques, enabling home monitoring environments consisting of inexpensive, low power, Vision Sensor Networks (VSNs).

Keywords: Learning and Adaptive Systems, Distributed Robot Systems, Autonomous Agents
Abstract: This paper explores methods and representations that allow two perceptually heterogeneous robots, each of which represents concepts via grounded properties, to transfer knowledge despite their differences. This is an important issue, as it will be increasingly important for robots to communicate and effectively share knowledge to speed up learning as they become more ubiquitous. We use Gärdenfors' conceptual spaces to represent objects as a fuzzy combination of properties such as color and texture, where properties themselves are represented as Gaussian Mixture Models in a metric space. We then use confusion matrices that are built using instances from each robot, obtained in a shared context, in order to learn mappings between the properties of each robot. These mappings are then used to transfer a concept from one robot to another, where the receiving robot was not previously trained on instances of the objects. We show in a 3D simulation environment that these models can be successfully learned and concepts can be transferred between a ground robot and an aerial quadrotor robot.

Keywords: Learning and Adaptive Systems, Behaviour-Based Systems, AI Reasoning Methods
Abstract: Reliable recognition of activities from cluttered sensory data is challenging and important for a smart home to enable various activity-aware applications. In addition, understanding a user’s preferences and then providing corresponding services is substantial in a smart home environment. Traditionally, activity recognition and preference learning were dealt with separately. In this work, we aim to develop a hybrid system which is the first trial to model the relationship between an activity model and a preference model so that the resultant hybrid model enables a preference model to assist in recovering performance of activity recognition in a dynamic environment. More specifically, on-going activity which a user performs in this work is regarded as high level contexts to assist in building a user’s preference model. Based on the learned preference model, the smart home system provides more appropriate services to a user so that the hybrid system can better interact with the user and, more importantly, gain his/her feedback. The feedback is used to detect if there is any change in human behavior or sensor deployment such that the system can adjust the preference model and the activity model in response to the change. Finally, the experimental results confirm the effectiveness of the proposed approach.

Keywords: Legged Robots, Underactuated Robots, Biologically-Inspired Robots
Abstract: In this paper, we present an under-actuated model of human walking, comprising only a soleus muscle and flexion/extension monoarticular hip muscles. The remaining muscle groups of the human leg are modeled using quasi-passive, series-elastic clutch elements. We hypothesize that series-elastic clutch units spanning the knee joint in a musculoskeletal arrangement can capture the dominant mechanical behaviors of the human knee in level-ground walking. Since the mechanical work done by the knee joint throughout a level-ground walking cycle is negative, and since there is no element capable of dissipating mechanical energy in the musculoskeletal model, biarticular elements would necessarily need to transfer energy from the knee joint to hip and/or ankle joints. This mechanism would reduce the necessary muscle work and improve the mechanical economy of a human-like walking robot. As an evaluation of these hypotheses, we vary model parameters, or spring constants, and muscle control parameters using an optimization scheme that maximizes walking distance and minimizes the mechanical economy of walking. We used a positive force feedback reflex control for the model’s soleus muscle, and upper body position control for the hip muscles. The model’s clutches were engaged/disengaged using simple state machine controllers. For model evaluation, a forward dynamics simulation was conducted at a moderate walking speed, and the resulting mechanics were compared to human walking data. The model makes qualitative predictions of joint mechanics, electromyography and mechanical economy.

Keywords: Legged Robots
Abstract: The performance of highly dynamic robotic machines is directly associated with both the actuation means and the specific mechanical properties/configuration of the system. Hydraulic actuation demonstrates significant competitive advantages when minimum weight and volume, large forces and wide range of speeds are required and this makes it very suitable for systems such as legged robots. The geometry and design of leg mechanisms have great effect on the actuation system performance such as the required flow, which directly determines the size/weight and power density, in turn affecting the performance of the robot. This paper describes the mechanism and operation principle of two 2-DOF legs considered for HyQ, a hydraulically actuated quadruped robot [1]. Numerical studies have been done to investigate the required flow, the pressure in the actuator chambers and the efficiency of the two leg mechanisms. The results show that the second leg design reduces the required flow significantly with less pressure-jump in the actuator and higher efficiency.

Keywords: Legged Robots, Biomimetics, Mechanism Design
Abstract: Most of traditional biped walkers based on passive dynamic walking have arc feet and locked ankle joints. In this paper, we propose the method to substitute the arc feet with flat feet. We hypothesize that the shape of the arc feet corresponds to a circular roll-over shape (ROS), which is a shape of a trajectory of center of pressure in the shankfixed frame. Firstly, we show that ankle joints driven by flexible muscles antagonistically can generate a circular ROS by simple simulation and real robot experiments. Radius of the ROS can be controlled by tension of the muscles. Then, we demonstrate stable 3D limit cycle walking by a biped robot with flat feet using the proposed ROS controlling method. We also investigated its behavior and stability when extra load is added to the robot and verified that the stability of the robot is maintained by keeping the ROS. The results suggest that the ROS can be a stability easure for limit cycle walkers to realize adaptive walking.

Keywords: Legged Robots, Mechanism Design, Intelligent Transportation Systems
Abstract: We report on the design of a leg-wheel hybrid platform Quattroped. Comparing to most hybrid platforms which have separate mechanisms of wheels and legs, this robot is implemented with a transformation mechanism which directly changes the morphology of wheels (i.e. a full circle) into 2 degree-of-freedom legs (i.e. combining two half-circles as a leg). The mechatronics, software infrastructure, and the initial experimental test of the robot are also reported.

Keywords: Calibration and Identification, Sensor Fusion, Legged Robots
Abstract: An accurate motion model is an important component in modern-day robotic systems, but building such a model for a complex system often requires an appreciable amount of manual effort. In this paper we present a motion model representation, the Dynamic Gaussian Mixture Model (DGMM), that alleviates the need to manually design the form of a motion model, and provides a direct means of incorporating auxiliary sensory data into the model. This representation and its accompanying algorithms are validated experimentally using an 8-legged kinematically complex robot, as well as a standard benchmark dataset. The presented method not only learns the robot's motion model, but also improves the model's accuracy by incorporating information about the terrain surrounding the robot.

Keywords: Micro/Nano Robots, Micro-manipulation, Calibration and Identification
Abstract: This paper presents the local stiffness measurements of Caenorhabditis Elegans (C. elegans) by buckling nanoprobes through the nanorobotic manipulation system inside an Environmental-Scanning Electron Microscope (E-SEM). C. elegans has complex outer and inner structures constructed by approximately one thousand cells. For example, the lateral alae are the surface fine structure by seam cell body. In this paper, their fine structures were observed by E-SEM directly; without any drying or dyeing processes. The observation environments are controlled under different E-SEM chamber pressures for clear observation of C. elegans. The local stiffness of C. elegans was measured by buckling measurement method of the nanoprobe fabricated by Focus Ion Beam (FIB) etching at the tip of Atomic Force Microscope (AFM) cantilever. The measurement position can arbitrarily be controlled by the nanorobotic manipulator inside the E-SEM. In this work, the local stiffness on or around the lateral alae were measured. From experimental results, the measured elasticity on lateral alae was 1.6 times larger than it around lateral alae. This local stiffness measurement technique can readily be applied to reveal unknown biological local stiffness, cell health conditions and novel cell diagnosis.

Keywords: Micro-manipulation, Force and Tactile Sensing, Force Control
Abstract: In a robotic cell injection system, the penetration force applied on the cell reflects the changes of the physical behavior of the cell. The force, if not controlled properly, may damage to the cells or even lead to death of the cells. The current cellular force measurement is limited by the inherent cantilever structure of the sensor, which may not be applicable to a practical cell injection system. In this paper, a simply supported beam structure based PVDF force sensor is first presented. The proportion relation is established between the penetration force and the sensor output after compensation. Using the designed force sensor, the force applied on the cell can be measured, and a force control based cell injection system is constructed. The experimental results performed on zebrafish embryos demonstrate the effectiveness of the micro force sensor and the force based control framework.

Keywords: Mechanism Design
Abstract: Recently, NOTES (Natural Orifice Translumenal Endoscopic Surgery) has attracted attention as a new approach in laparoscopic surgery. This approach achieves extremely less invasive surgery, however, manipulation of forceps is very difficult in NOTES, which brings more burdens on the surgeons. Under these situations, the aim of this study is to develop a micro mobile robot that could move in the abdominal cavity, loaded with a camera and/or forceps. In order to achieve stable movements and surgery support actions, we proposed using peritoneum (abdominal wall) as the surface for moving in the abdominal cavity. Moreover, we devised a robot system that relies on two suckers to attach to the peritoneum, and a cable driven mechanism to realize the relative movement of the two suckers, by which 3 D.O.F. (Degree Of Freedom) movements, i.e., moving forward/backward, turning left/right, and moving up/down could be realized. After examining the suction availability of suckers employed, we built a prototype robot system. We verified that, hanging upside down on the surface of vinyl wall, the robot could accomplish the designated movements with a certain load, which showed potential of using the robot system as the surgery support for NOTES.

Keywords: Micro/Nano Robots
Abstract: In this paper, we presented a design for an automated cell supply system that can be used with complex microfluidic applications requiring single cell loading such as the current nuclear transplantation method. The aim of the system is to automatically transfer mammalian donor (~15µm) or egg (~100µm) cells one by one from a container to a PDMS micro-channel and then transport them to other modules. The system consists of two main parts; a single cell suction module, and a PDMS-based microfluidic chip controlled by an external pump. The desired number of vacuumed cells can be directed into the microfluidic chip and stored in a docking area. From the batch, they can be moved to next module by activating pneumatic pressure valves located on two sides of the chip. The entire mechanism is combined with monitoring systems that perform the detection/tracking and control program.

Keywords: Micro/Nano Robots, Micro-manipulation
Abstract: In this study, we successfully produced a functional microtool made of gel microbeads using size-dependent microparticle classification. Gel microbeads are made by salting-out hydrophilic photo-crosslinkable resin ENT-3400. These gel microbeads were separated according to their size using microfilters made of polydimethylsiloxane (PDMS). The first filter is a row of fluidic microchannels that block microbeads with a size greater than the channel’s width. Another filtration method has been examined using a magnetically driven microtool (MMT) to separate the beads using the centrifugal force created by this MMT actuated with a DC motor. Separated gel microbeads were recovered after filtration and used to fabricate functional microtools, for example, a tether-shaped gel tool, by contact with other gel microbeads under UV illumination. The produced gel tool is manipulated using optical tweezers in a microchip. We successfully achieved size-dependent separation of gel microbeads and production of a tether-shaped gel tool.

Keywords: Surveillance Systems, Recognition
Abstract: This paper describes an efficient method for retrieving the 3-dimensional shape associated to novelties in the environment of an autonomous robot, which is equipped with a laser range finder. First, changes are detected over the point clouds using a combination of the Gaussian Mixture Model (GMM) and the Earth Mover’s Distance (EMD) algorithms. Next, the shape retrieval is achieved using two different algorithms. First, new samplings are generated from each Gaussian function, followed by a Random Sampling Consensus (RANSAC) algorithm to retrieve geometric primitives. Furthermore, a new algorithm is developed to directly retrieve the shape according to the mathematical space of Gaussian mixture. In this paper, the set of geometric primitives has been limited to the set C = {sphere, cylinder, plane}. The two shape retrieval methods are compared in terms of computational cost and accuracy. Experimental results in various real and simulated scenarios demonstrate the feasibility of the approach.

Keywords: Recognition, Computer Vision
Abstract: The real time requirement is an additional constraint on many intelligent applications in robotics, such as shape recognition and retrieval using a mobile robot platform. In this paper, we present a scalable approach for efficiently retrieving closed contour shapes. The contour of an object is represented by piecewise linear segments. A skip Tri-Gram is obtained by selecting three segments in the clockwise order while allowing a constant number of segments to be ``skipped'' in between. The main idea is to use skip Tri-Grams of the segments to implicitly encode the distant dependency of the shape. All skip Tri-Grams are used for efficiently retrieving closed contour shapes without pairwise matching feature points from two shapes. The retrieval is at least an order of magnitude faster than other state-of-the-art algorithms. We score 80% in the Bullseye retrieval test on the whole MPEG 7 shape dataset [11]. We further test the algorithm using a mobile robot platform in an indoor environment. 8 objects are used for testing from different viewing directions, and we achieve 82% accuracy.

Keywords: Recognition, Range Sensing, Service Robots
Abstract: A mobile robot that accomplishes high level tasks needs to be able to classify the objects in the environment and to determine their location. In this paper, we address the problem of online object detection in 3D laser range data. The object classes are represented by 3D point-clouds that can be obtained from a set of range scans. Our method relies on the extraction of point features from range images that are computed from the point-clouds. Compared to techniques that directly operate on a full 3D representation of the environment, our approach requires less computation time while retaining the robustness of full 3D matching. Experiments demonstrate that the proposed approach is even able to deal with partially occluded scenes and to fulfill the runtime requirements of online applications.

Keywords: Recognition, Force and Tactile Sensing, Grasping
Abstract: In situations where generating in internal representation of an object's shape can not be carried out via visual methods, such as in low light conditions or due to a hardware fault, an internal representation of the object must be built from tactile information alone. Existing methods for doing so rely on the availability of a complete force sensitive skin. The work described in this paper shows a method that requires no such equipment and in fact requires no external sensors at all. The method demonstrates that an accurate representation of the object can be built with the accuracy depending on the number of attempts at contacting the object. This internal representation of object can then be used for other tasks such as planning grasps.

Keywords: Recognition, Computer Vision, Grasping
Abstract: This paper describes a robotic system that learns visual models of symmetric objects autonomously. Our robot learns by physically interacting with an object using its end effector. This departs from eye-in-hand systems that move the camera while keeping the scene static. Our robot leverages a simple nudge action to obtain the motion segmentation of an object in stereo. The robot uses the segmentation results to pick up the object. The robot collects training images by rotating the grasped object in front of a camera. Robotic experiments show that this interactive object learning approach can deal with top-heavy and fragile objects. Trials confirm that the robot-learned object models allow robust object recognition.

Keywords: Recognition, Sensor Fusion, Localization
Abstract: Self-location is very informative for wearable systems. In this paper, we propose a method for identifying user's location from omnidirectional image sensor, GPS data and wireless LAN data. Azimuth-invariant features are extracted from an omnidirectional image by integrating pixel information circumferentially, and then its location is independently recognized from the omnidirectional image feature, GPS data and wireless LAN data projected into a sub-space made from learning data. We show the effectiveness of our method by experimental results in real data.

Keywords: Recognition, Computer Vision, Learning and Adaptive Systems
Abstract: In this paper we describe the problem of Visual Place Categorization (VPC) for mobile robotics, which involves predicting the semantic category of a place from image measurements acquired from an autonomous platform. For example, a robot in an unfamiliar home environment should be able to recognize the functionality of the rooms it visits, such as kitchen, living room, etc. We describe an approach to VPC based on sequential processing of images acquired with a conventional video camera. We identify two key challenges: Dealing with non-characteristic views and integrating restricted-FOV imagery into a holistic prediction. We present a solution to VPC based upon a recently-developed visual feature known as CENTRIST (CENsus TRansform hISTogram). We describe a new dataset for VPC which we have recently collected and are making publicly available. We believe this is the first significant, realistic dataset for the VPC problem. It contains the interiors of six different homes with ground truth labels. We use this dataset to validate our solution approach, achieving promising results.

Keywords: Range Sensing, Mapping
Abstract: An alternative to the conventional quantization for occupied voxel lists in both 2D and 3D is presented. The performance metrics of the hexagonal lattice in 2D and the face centred and body centred cubic lattices in 3D are investigated and compared to their square and cubic counterparts. It is found that quantization to alternative lattices yields some improvements. Ultimately, the D3 or face centred cubic lattice is highlighted for its lower quantization error, lower rotation variability and higher order rotational symmetry. It has three times less occupied voxel count pose variability than a standard cubic occupied voxel list. These improvements have implications for SLAM and path planning.

Keywords: Range Sensing, Sensor Fusion, Recognition
Abstract: In this paper, we investigate the problem of 3D object categorization of objects typically present in kitchen environments, from data acquired using a composite sensor. Our framework combines different sensing modalities and defines descriptive features in various spaces for the purpose of learning good object models. By fusing the 3D information acquired from a composite sensor that includes a color stereo camera, a time-of-flight (TOF) camera, and a thermal camera, we augment 3D depth data with color and temperature information which helps disambiguate the object categorization process. We make use of statistical relational learning methods (Markov Logic Networks and Bayesian Logic Networks) to capture complex interactions between the different feature spaces. To show the effectiveness of our approach, we analyze and validate the proposed system for the problem of recognizing objects in table settings scenarios.

Keywords: Recognition, Learning and Adaptive Systems, Dexterous Manipulation
Abstract: Task learning from observations of non-expert human users will be a core feature of future cognitive robots. However, the problem of task segmentation has only received minor attention. In this paper, we present a new approach to classifying and segmenting series of observations into a set of candidate motions. As basis for these candidates, we use Structured UKR manifolds, a modified version of Unsupervised Kernel Regression which has been introduced in order to easily reproduce and synthesise represented dextrous manipulation tasks. Together with the presented mechanism, it then realises a system that is able both to reproduce and recognise the represented motions.

Keywords: Distributed Robot Systems, Networked Robots, Sensor Networks
Abstract: We describe a distributed boundary detection algorithm suitable for use on multi-robot systems with dynamic network topologies. We assume that each robot has access to its local network geometry, which is the combination of a robot's network connectivity and the positions of its neighbors measured relative to itself. Our algorithm uses this information to classify robots as boundary or interior in one communications round, which is fast enough for rapidly changing networks. We use the local boundary classifications to create a robust boundary subgraph, and to determine if the boundary is an interior void or the exterior boundary. A proof of the key property of the boundary detection algorithm is provided, and all the algorithms are extensively tested on a swarm of 25-35 robots in rapidly changing network topologies.

Keywords: Distributed Robot Systems, Autonomous Agents, AI Reasoning Methods
Abstract: Coalition formation algorithms are generally not applicable to real-world robotic collectives since they lack mechanisms to handle uncertainty. Those mechanisms that do address uncertainty either deflect it by soliciting information from others or apply reinforcement learning to select an agent type from within a set. This paper presents a coalition formation mechanism that directly addresses uncertainty while allowing the agent types to fall outside of a known set. The agent types are captured through a novel agent modeling technique that handles uncertainty through a belief-based evaluation mechanism. This technique allows for uncertainty in environmental data, agent type, coalition value, and agent cost. An investigation of both the effects of adding agents on processing time and of model quality on the convergence rate of initial agent models (and thereby coalition quality) is provided. This approach handles uncertainty on a larger scale than previous work and provides a mechanism readily applied to a dynamic collective of real-world robots.

Keywords: Distributed Robot Systems, Control Architectures and Programming, Cellular and Modular Robots
Abstract: The goal of a robot formation control architecture is to get a number of robots into a specified form. To be effective and practical, the control architecture must be able to transition a group of robots from an initial swarm to a final formation. It must then be able to handle real-world events that could disrupt the formation, thus, requiring formation repair, obstacle avoidance, and changes in the formation. In previous work, we presented a distributed, reactive cellular automata-based formation control architecture capable of controlling any number of robots in formation at once. In this paper, we examine our architecture with respect to necessary characteristics to handle real-world occurrences. To address issues of formation repair and obstacle avoidance, the control architecture is extended by a distributed auctioning method that allows the robot formation to reconfigure autonomously.

Keywords: Distributed Robot Systems, Cooperating Robots, Intelligent Transportation Systems
Abstract: In this paper, we study task allocation problems where cooperative robots need to execute complex tasks simultaneously. We first review the concepts and properties of reaction functions proposed in the literature. Then, we develop a distributed negotiation procedure for robots to finds all possible task exchanges that can reduce the team cost of a given task allocation. Finally, we demonstrate empirically that the negotiation procedure can reduce the team costs of existing task-allocation algorithms substantially.

Keywords: Distributed Robot Systems, Cooperating Robots, Agent-Based Systems
Abstract: In multi-robot systems, task allocation and coordination are two fundamental problems that share high synergy. Although multi-robot architectures typically separate them into distinct layers, relevant improvement may be expected from solutions that are able to concurrently handle them at the same "level". This paper proposes a novel framework, called CoMutaR (Coalition formation based on Multi-tasking Robots), which is used for both tackle task distribution among teams of mobile robots, and to guarantee the coordination within the formed teams.

Robot capabilities are modelled as actions, independent modules whose inputs do not depend on the robot that generated it. Solutions to tasks are devised as coalitions of actions, that can be spread amongst the available robots. We also define the concept of share-restricted resources, which are periodically checked and updated by the actions in the system. In contrast to prior approaches, this mechanism enables to quickly determine if two actions can be executed simultaneously, allowing a single robot to execute multiple tasks concurrently. A single-round auction protocol is used to automatically discover and form coalitions. Once a coalition is formed, coordination among robots is modelled as constraints imposed over the share-restricted resources. Finally, we have successfully implemented and applied CoMutaR in typical scenarios like object transportation, area surveillance, and multi-robot box pushing. Experimental results demonstrate that the system is able to provide good solutions even in the case of severe failures in participating robots.

Keywords: Distributed Robot Systems, Networked Robots
Abstract: The paper studies formation control of multi-agent systems under a directed acyclic graph. In a directed acyclic graph, the agents without neighbors are leaders and the others are followers. Leaders move in a formation with a time-varying velocity and followers can access the relative positions of their neighbors and the leaders' velocity. A local formation control law is proposed in the paper based on pursuit strategies and necessary and sufficient conditions for stability and convergence are derived. Moreover, the results are extended to the case with arbitrary communication delays, for which the steady-state formation is presented according both the control parameters and time delays.

Keywords: Cooperating Robots, Nonholonomic Motion Planning, Path Planning for Multiple Mobile Robot Systems
Abstract: This paper describes a leader-follower based formation control framework to coordinate multiple nonholonomic mobile robots. The proposed strategy deploys a control theoretic bottom-up approach where, continuous controllers are coordinated by a supervisory control of discrete event systems. All the mobile robots are required to navigate in an obstacle populated environment. And the followers keep a predetermined geometric formation with the leader while being adaptable to the constraints imposed by obstacles on the environment.

In order to achieve proper navigation, we develop a set of behavior based low-level continuous controllers while the higher-level discrete event system manages the dynamic interaction with the external environment. The use of discrete event systems reflects a modular manageable system with the potential for scalability and reusability. The proposed system is implemented through simulation and the results are shown to verify its operation.

Keywords: Navigation, Networked Robots
Abstract: We consider the problem of sensor-aware path planning for a robot in a Networked Robot System, in particular in urban environments equipped with a network of surveillance cameras. A robot can use observations from the camera network to improve its own localization performance, but also needs to take into account the specifics of its local sensors. We model our problem in the Markov Decision Process framework, which forms a natural way to express concurrent and possibly conflicting objectives--such reaching a goal quickly, keeping the robot localized, keeping the target in sight--each with their own priority. We show how we can successfully prioritize the different objectives in a flexible way by changing the reward function, based on the sensory needs of the system.

Keywords: Distributed Robot Systems, Autonomous Agents, Sensor Networks
Abstract: Target tracking is an important task in sensor networks, especially in mobile sensor networks. Flocking control is used to control a mobile sensor network to track a target. However, there are some existing problems in this control method, such as network fragmentation, loss of formation and poor tracking performance. In order to handle these problems we propose a novel approach to flocking control of a mobile sensor network to track a moving target within changing environments. In our approach, each agent can cooperatively learn the network's parameters to decide the size of network in a decentralized fashion so that the connectivity, formation and tracking performance can be improved when avoiding obstacles. In addition, to demonstrate the benefit of our approach a comparison between this approach and the existing method is given. Computer simulations are performed to demonstrate the effectiveness of the proposed approach.

Keywords: Distributed Robot Systems, Navigation, Networked Robots
Abstract: The goal of this paper is to serve as a reference for researchers in robotics and control that are interested in realistic modeling, theoretical analysis and simulation of wireless links. To realize the full potentials of networked robotic systems, an integration of communication issues with motion planning/control is necessary. While considerable progress has been made in the area of networked robotic systems, communication channels are typically considered ideal or ideal within a certain radius of the transmitter, both considerable oversimplifications of wireless channels. It is the goal of this paper to provide a comprehensive overview of the key characteristics of wireless channels, as relevant to networked robotic operations. In particular, we provide a probabilistic framework for characterization of the underlying multi-scale dynamics of a wireless link: small-scale fading, large-scale fading and path loss. We furthermore confirm these mathematical models with channel measurements made in our building. We also discuss channel characterization based on the knowledge available on the geometry and dielectric properties of the environment.

Keywords: Rehabilitation Robotics, Motion Control, Wheeled Robots
Abstract: This paper presents mechanism and control of a Four-Wheel-Drive (4WD) robotic platform for wheelchairs. The 4WD mechanism equips four wheels, two omni-wheels in front and two normal tires in rear. The normal wheel and the omni-wheel, mounted on the same side of the base, are interconnected by a synchro-drive transmission to rotate in unison with a drive motor. To control chair orientation on the 4WD platform, the third motor is installed on the platform. The chair with the proposed omnidirectional 4WD system is capable of moving in any direction which is so-called holonomic and omnidirectional mobility. The holonomic omnidirectional mobile capability enables a person to drive a mobile system with no knowledge about the drive mechanism or its configuration since it can move in any direction and rotate from any configuration of the mechanism. This paper presents the mechanism and control of 4WD platform to which powered-caster omnidirectional control is applied. The rotations of two pairs of wheel and vertical axis of a chair are controlled in such a way that it performs as a powered twin-caster to realize holonomic motions. The prototype wheelchair is designed and built to verify the mechanism design and control method. The smooth and flexible onidirectional motions are presented by the experioments.

Keywords: Motion Control, Wheeled Robots, Redundant Robots
Abstract: The paper describes a stabilization control of two wheels driven wheelchair based on pitch angle disturbance observer (PADO). PADO make it possible to stabilize the wheelchair motion and remove casters. This brings a sophisticated mobility of wheelchair because the casters are obstacle to realize step passage motion and so on. The proposed approach based on PADO is robust against disturbance of pitch angle direction and the more functional wheelchairs is expected in the developed system. The validity of the proposed method is confirmed by simulation and experiment.

Keywords: Legged Robots, Motion Control, Range Sensing
Abstract: This paper describes an approach of motion stabilization by using laser distance sensor for biped robots with flexible ankle joints. For avoiding the vibrated Zero Moment Point (ZMP) behavior due to the mechanical resonance, the vibration control method is proposed in the paper. The deviated center of gravity (COG) due to the ankle's deflection is measured in real-time by laser distance sensor, and equivalent reaction force relating to COG deviation is used as feedback signal for vibration control. The reaction force feedback also enables the regulation of the compliant property of the robots. Therefore the proposed approach is suitable to stabilize the walking behavior including the impact between foot and floor environments. The validity is evaluated by several experimental results.

Keywords: Recognition, Navigation
Abstract: For manipulation of remote mobile robots, adequate scheduling of tasks and selecting of operational commands are required. This paper presents an analysis procedure to make the task switching profile visible by utilizing the Self-Organizing Map (SOM) and new cluster growing method. For practical verification, an experiment system with radio-controlled construction equipments was built, and the proposed analysis procedure was applied to the experimental task. As a result, it was confirmed by correlation analysis that distances among decomposed clusters corresponding to segments of operation strongly relate to performance index of the task.

Keywords: Intelligent Transportation Systems, Intelligent Vehicles
Abstract: To reduce rear-end crash of automobiles, it is important to judge necessity of deceleration assistance as earlier as possible and initiate the assistance naturally. On the other hand, we have derived a mathematical model of driver’s perceptual risk of proximity in car following situation and successfully derived driver deceleration model to describe deceleration patterns and brake initiation timing of expert driver. In this research, an automatic braking system for collision avoidance will be proposed based on the formulated brake profile model and brake initiation model of expert driver to realize smooth, secure brake assistance naturally. It will be shown that the proposed control method can generate smooth profile for various conditions. In addition, experimental results using a driving simulator will show validity of the proposed system based on subjective evaluation.

Keywords: Navigation, Robotics in Hazardous Fields
Abstract: For an autonomous vehicle navigating in a static environment for which an a priori map is inaccurate, we propose a hybrid receding horizon control method to determine optimal routes when new obstacles are detected. The hybrid method uses the level sets of the solution to either a global or local Eikonal equation in the formulation of the receding horizon control problem. Whenever an obstacle is detected along the path of the autonomous vehicle, a solution to a local Eikonal equation is used to determine whether a new, global Eikonal equation must be solved for use in the receding horizon optimization problem. The decision to select a new level set solution is made based on certain matching conditions that guarantee the optimality of the path. The selection of a global or local solution to the Eikonal equation induces a hybrid system structure in the control formulation. We rigorously prove sufficient conditions that guarantees that the vehicle will converge to the goal as long as the goal is accessible. In the end, simulation results are discussed.

Keywords: AI Reasoning Methods, Field Robots, Navigation
Abstract: In this paper we introduce Focused A* Heuristic Recomputation (FAHR),

an enhancement to A* search that can detect and correct large

discrepancies between the heuristic cost-to-go estimate and the true

cost function. In situations where these large discrepancies exist,

the search may expend significant effort escaping from the ``bowl'' of

a local minimum. A* typically computes supporting data structures for

the heuristic once, prior to initiating the search. FAHR directs the

search out of the bowl by recomputing parts of the heuristic function

opportunistically as the search space is explored.

FAHR may be used when the heuristic function is in the

form of a pattern database.

We demonstrate the

effectiveness of the algorithm through experiments on a ground vehicle

path planning simulation.

Keywords: Evolutionary Robotics, Animation and Simulation, Adaptive Control
Abstract: This paper introduces a novel and flexible simulation platform for studying pursuit and evasion in unknown 2-D environments of arbitrary obstacles, in an effort to expand the practical application of pursuit-evasion research. The platform provides realistic simulation of the sensing capability of each robotic agent (either a pursuer or an evader). Each agent uses real-time local sensing to collect information from the environment while it simultaneously plans and executes its motion to best satisfy one or more objectives. The evader's objectives are to reach a specific goal location as quickly as possible and to avoid being caught by the pursuer. The pursuer's objectives are to locate and capture the evader whose motion is unknown, and when the evader is not seen, explore the environment and predict where the evader may be. Under a common real-time planning paradigm, each agent's planner dynamically adapts its goals and objectives to the agent's changing circumstances so that the agent can always choose the best course of action. Simulation results have shown that the introduced approach is an effective means to study sophisticated pursuit-evasion scenarios and accomplish objectives for both the pursuer and the evader in an unknown environment. The platform can be easily expanded to accommodate multiple agents in more complex pursuit-evasion tasks.

Keywords: Navigation, Mapping, Field Robots
Abstract: This paper proposes a novel approach, Simultaneous Path Planning and Topological Mapping (SP2ATM), to address the problem of path planning by registering the topology of the perceived dynamic environment as opposed to the conventional grid representation. The local topology is encoded, concurrent and incremental with path planning, by extracting only the admissible free space. The resulting Admissible Space Topological Map (ASTM) then serves as the minimum information to facilitate path planning in the 3D configuration space. Experimental results obtained from our mobile robot X1 in a complex planar environment, validates completeness and optimality of the algorithm.

Keywords: Nonholonomic Motion Planning, Navigation
Abstract: This paper presents a method for improving the runtime of an optimal heuristic path planner (A*) so that it can run repeatedly, in real-time, in a dynamic environment. This is necessary for mobile robots navigating in dynamic environments that have moving obstacles with associated costs, such as personal space around people or buffer zones around dangerous vehicles. Our approach is to modify the search space used by the A* algorithm, increasing the size of grid cells further from the robot. This approach relies on the notion that only the area closest to the robot needs to be searched carefully; areas further from the robot can be searched more coarsely. Because the planner is assumed to run repeatedly as the robot moves, the robot will always have a fine-grained path defined for its next action. We have experimentally verified in simulation that this algorithm can be run in real-time and produces paths that are comparable to full-resolution planning.

Keywords: SLAM, Mapping
Abstract: This paper introduces an approach that reduces the size of the state and maximizes the sparsity of the information matrix in exactly sparse delayed-state SLAM. We propose constant time procedures to measure the distance between a given pair of poses, the mutual information gain for a given candidate link, and the joint marginals required for both measures. Using these measures, we can readily identify non redundant poses and highly informative links and use only those to augment and to update the state, respectively. The result is a delayed-state SLAM system that reduces both the use of memory and the execution time and that delays filter inconsistency by reducing the number of linearization introduced when adding new loop closure links. We evaluate the advantage of the proposed approach using simulations and data sets collected with real robots.

Keywords: SLAM, Localization, Field Robots
Abstract: In this paper we present a Simultaneous Localization And Mapping (SLAM) application using data obtained from a microwave radar sensor. The radar scanner is based on the Frequency Modulated Continuous Wave (FMCW) technology. In order to meet the needs of radar image analysis complexity, a trajectory-oriented EKF-SLAM technique using data from a 360° field of view radar sensor has been developed. This process makes no landmark assumptions and avoids the data association problem. The method of egomotion estimation makes use of the Fourier-Mellin Transform for registering radar images in a sequence, from which the rotation and translation of the sensor motion can be estimated. In the context of the scan-matching SLAM, the use of the Fourier-Mellin Transform is original and provides an accurate and efficient way of computing the rigid transformation between consecutive scans. Experimental results on real-world data are presented. Moreover a performance evaluation of the results is carried out. A comparative study between the output data of the proposed method and the data processed with smoothing approaches to SLAM is also achieved.

Keywords: SLAM, Adaptive Control, Dynamics
Abstract: This paper proposes a solution to a door crossing problem in unknown environments for an autonomous wheelchair. The problem is solved by a dynamic path planning algorithm implementation based on successive frontier points determination. An adaptive trajectory tracking control based on the dynamic model is implemented on the vehicle to direct the wheelchair motion along the path in a smooth movement. An EKF feature-based SLAM is also implemented on the vehicle which gives an estimate of the wheelchair pose inside the environment. The SLAM allows the map reconstruction of the environment for future safe navigation purposes. The entire system is evaluated in a real time simulator of a robotic wheelchair.

Keywords: SLAM, Mapping, Localization
Abstract: Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM~(simultaneous localization and mapping) which does not require motion or odometry information but only a sequence of noisy measurements from visited places. We propose a particle filtering technique for topological SLAM which relies on a method for disambiguating places which appear indistinguishable using neighbourhood information extracted from the sequence of observations. The algorithm aims to induce a small topological map which is consistent with the observations and simultaneously estimate the location of the robot.

The proposed approach is evaluated using a data set of sonar measurements from an indoor environment which contains several similar places. It is demonstrated that our approach is capable of dealing with severe ambiguities and, and that it infers a small map in terms of vertices which is consistent with the sequence of observations.

Keywords: SLAM, Localization, Mapping
Abstract: We present a method for topological SLAM that specifically targets loop closing for edge-ordered graphs. Instead of using a heuristic approach to accept or reject loop closing, we propose a probabilistically grounded multi-hypothesis technique that relies on the incremental construction of a map/state hypothesis tree. Loop closing is introduced automatically within the tree expansion, and likely hypotheses are chosen based on their posterior probability after a sequence of sensor measurements. Careful pruning of the hypothesis tree keeps the growing number of hypotheses under control and a recursive formulation reduces storage and computational costs. Experiments are used to validate the approach.

Keywords: Humanoid Robots, Legged Robots, Motion Control
Abstract: SURALP is a new walking humanoid robot platform designed at Sabanci University - Turkey. The kinematic arrangement of the robot consists of 29 independently driven axes, including legs, arms, waist and a neck. This paper presents the highlights of the design of this robot and experimental walking results. Mechanical design, actuation mechanisms, sensors, the control hardware and algorithms are introduced. The actuation is based on DC motors, belt and pulley systems and Harmonic Drive reduction gears. The sensory equipment consists of joint encoders, force/torque sensors, inertial measurement systems and cameras. The control hardware is based on a dSpace digital signal processor. A smooth walking trajectory is generated. A variety of controllers for landing impact reduction, body inclination and Zero Moment Point (ZMP) regulation, early landing trajectory modification, and foot–ground orientation compliance and independent joint position controllers are employed. A posture zeroing procedure is followed after manual zeroing of the robot joints. The experimental results indicate that the control algorithms presented are successful in improving the stability of the walk.

Keywords: Humanoid Robots, Medical Robots and Systems, Biologically-Inspired Robots
Abstract: Abstract— This paper deals with a research work aimed to develop a new three degrees of freedom (DOF) mechanism for humanoid robots. The main idea is to build hybrid (3DOF) mechanism, which avoids the drawbacks of the serial and parallel mechanisms. The new solution has to merge the advantages of both classical (serial and parallel) structures in order to achieve optimal performances. The proposed mechanism can be used as a solution for several modules in humanoid robot. The hip mechanism is taken as an example to illustrate the contribution of this paper. To evaluate the performances of the system, simulation of this new mechanism is carried out with Adams software. Geometrical and Kinematic models are developed and included in the simulation tool. Based on biomechanical data, analysis of the new kinematic structure is carried out. The design of the proposed solution is then described. Finally the first prototype developed for the HYDROïD robot’s hip is presented. This mechanism is a part of an International patent accepted at INPI- France.

Keywords: Humanoid Robots, Legged Robots, Mechanism Design
Abstract: The “iCub” is a robotic platform that was developed within the RobotCub European project to provide the cognition research community with an open child humanoid platform for understanding and development of cognitive systems. In this paper we present the mechanical realization of the new lower body developed for the “iCub” child humanoid robot in order to keep up with the latest technology and solve mechatronic problems found in the previous version. The new lower body assembly demonstrates significant improvements over the old prototype including higher modularity, full joint state sensing, improved range of motion and torque capabilities. In particular the new leg and waist mechanisms to match the size and physical abilities of a 3½ year old human child are introduced.

Keywords: Humanoid Robots, Mechanism Design, Motion Control
Abstract: Abstract—Designing and control of biped robot are still open questions. Design of ankle joint which is considered one of the more compact with high power capacity and low weight is a big challenge. The very important role played by this joint during walking, makes its design and control the first step of having a robust walking biped. In this paper, a novel three dof hybrid mechanisms has been proposed. This mechanism is actuated hydraulically and uses cable technology for power transmission. The proposed solution fulfils the requirements induced by both geometrical and biomechanical constraints. At first, the geometrical and kinematics properties of the proposed solution have been developed. A simulation tool has been built using ADAMS software and used to carry out early design dimensioning of the several components. Singularity study is detailed showing the advantage of this new solution. Control method has been proposed and tested. Finally manufactured prototype of this solution is presented with preliminary results showing the performances of the mechanism. This mechanism is a part of an International patent accepted at INPI- France.

Keywords: Humanoid Robots, Force and Tactile Sensing, Mechanism Design
Abstract: In order for robots to be able to assist humans at a very close distance, robots should allow contacts occurred at many places and deal with them. For realizing such functions, robots should have whole-body soft sensor exterior for preparing contacts against almost every body parts since it is difficult to limit where to be touched from humans.

Although several groups have developed humanoid type robots which have soft tactile sensors, most of them detects distributed 1-axis forces and that is not sufficient when the robot and a human have contacts very closely. In addition to that, there is no consideration in the previous studies about humans' movement during close contact with the robots.

In order to solve these problems, we have newly developed a humanoid with soft 3D-deformable sensor flesh and automatic recoverable mechanical overload protection mechanism. Soft 3D-deformable sensors are implemented by molding the infrared light receiving devices into the urethane cube and by detecting the changes of the output voltage of the devices during the deformation. On the other hand, automatic recoverable mechanical overload protection mechanism is implemented by small mechanical torque limiters and monitoring system for embedded potentiometers in the torque limiters. Also detail implementation of the embedded electric system and the overall software structure is described in this paper.

Keywords: Social Human-Robot Interaction, Gesture, Posture, Social Spaces and Facial Expressions, Robot Companions and Social Robots in Home Environments
Abstract: Human movement analysis through vision sensing systems is an important subject regarding Human-Robot interaction. This is a growing area of research, with wide range of aplications fields. The ability to recognize human actions using passive sensing modalities, is a decisive factor for machine interaction. In mobile platforms, image processing is regarded as a problem, due to constant changes.We propose an approach, based on Horopter technique, to extract Regions Of Interest (ROI) delimiting human contours. This fact will allow tracking algorithms to provide faster and accurate responses to human feature extraction. The key features are head and both hand positions, that will be tracked within image context. Posterior to feature acquisition, they will be contextualized within a technique, Laban Movement Analysis (LMA) and will be used to provide sets of classifiers. The implementation of the LMA techquine will be based on Bayesian Networks. We will use these bayesian classifiers to label/classify human emotion within the context of expressive movements. Compared to full image tracking, results improved with the implemented approach, the horopter and consequently so did classification results.

Keywords: Cognitive Human-Robot Interaction, Social Human-Robot Interaction, Learning and Adaptive Systems
Abstract: A joint learning approach is described that meets a major challenge with social robots --- developing a methodology for learning communicative behaviors. We focus on interaction rule that is relationship between a robot's action and a partner's response. In this approach a robot is simultaneously a learner and proposer of interaction rules. The human partner and robot continuously search for and co-create new rules as inspired by the social games played between an infant and a caregiver. A simple and universal scheme with response prediction and habituation/dishabituation was developed, and a robot model was built using the scheme. The robot generates actions, observes the partner's response, and get to predict them. It identifies relationships between its actions and the responses, and generates actions designed to elicit particular responses from the partner. After it is habituated to the responses, it generates other actions to search for other rules. In experiments of human-robot interaction based on this model and using a ball, different patterns of interaction emerged, such as passing the ball back and forth, rolling and catching, and feint passing. Response prediction and appropriate habituation supported the emergence of interactions, indicating that the scheme and the model are effective. This joint learning should lead to natural communication between human partners and social robots beyond teach/taught relationship.

Keywords: Cognitive Human-Robot Interaction, Social Human-Robot Interaction, Gesture, Posture, Social Spaces and Facial Expressions
Abstract: Previous work shows that the movement representation in task spaces offers many advantages for learning object-related and goal-directed movement tasks through imitation. It allows to reduce the dimensionality of the data that is learned and simplifies the correspondence problem that results from different kinematic structures of teacher and robot. Further, the task space representation provides a first generalization, for example wrt. differing absolute positions, if bi-manual movements are represented in relation to each other. Although task spaces are widely used, even if they are not mentioned explicitly, they are mostly defined a priori. This work is a step towards an automatic selection of task spaces. Observed movements are mapped into a pool of possibly even conflicting task spaces and we present methods that analyze this task space pool in order to acquire task space descriptors that match the observation best. As statistical measures cannot explain importance for all kinds of movements, the presented selection scheme incorporates additional criteria such as an attention-based measure. Further, we introduce methods that make a significant step from purely statistically-driven task space selection towards model-based movement analysis using a simulation of a complex human model. Effort and discomfort of the human teacher is being analyzed and used as a hint for important task elements. All methods are validated with realworld data, gathered using color tracking with a stereo vision system and a VICON motion capturing system.

Keywords: Gesture, Posture, Social Spaces and Facial Expressions, Service Robots, Robot Companions and Social Robots in Home Environments
Abstract: In human-robot interaction, robots often fail to lead humans to intended reactions due to their limited ability to express affective nuances. In this paper, we propose a motion modification method that combines affective nuances with arbitrary motions of humanoid robots to induce humans to intended reactions by expressing affective states. The method is applicable to various humanoid robots that differ in degrees of freedom or appearances, and the affective nuances are parametrically expressed in a two-dimensional model comprised of valence and arousal. The experimental results showed that the desired affective nuances could be expressed by our method, but it also suggested some limitations. We believe that the method will contribute to interactive systems in which robots can communicate with appropriate expressions in various contexts.

Keywords: Service Robots, Gesture, Posture, Social Spaces and Facial Expressions, Voice, Speech Synthesis and Recognition
Abstract: This paper presents our expressive facial speech synthesis system Eface, for a social or service robot. Eface aims at enabling a robot to deliver information clearly with empathetic speech and an expressive virtual face. The empathetic speech is built on the Festival speech synthesis system and provides robots the capability to speak with different voices and emotions. Two versions of a virtual face have been implemented to display the robot’s expressions. One with just over 100 polygons has a lower hardware requirement but looks less natural. The other has over 1000 polygons; it looks realistic, but costs more CPU resource and requires better video hardware. The whole system is incorporated into the popular open source robot interface Player, which makes client programs easy to write and debug. Also, it is convenient to use the same system with different robot platforms. We have implemented this system on a physical robot and tested it with a robotic nurse assistant scenario.

Keywords: Biologically-Inspired Robots, Kinematics, Legged Robots
Abstract: Salamanders propel themselves by proper coordination of limb movements and body undulations. This type of locomotion is interesting for robotics to design robots capable of locomotion on water and land. In this work we identify the control and structural parameters that contribute to forward terrestrial locomotion. We introduce a kinematic model of Salamandra robotica II, a new salamander robot, to explore how the stride length varies with different limb sizes and different types of body oscillations. We also perform systematic tests using a dynamic model built in a physics-based simulator to analyze the locomotion performance in terms of forward speed and power consumption. The results show that it is beneficial to use body undulations with variable curvature along the body, and that the tail can serve as a fifth limb to provide thrust on ground. Experiments using the real robot validate the simulation results and the contribution of the proposed control strategies.

Keywords: Biologically-Inspired Robots, Kinematics
Abstract: Based on the modular concept, this paper presents two caterpillar robot prototypes which are inspired by two typical caterpillars: Inchworm and Pine Caterpillar. The inchworm robot prototype features simplest kinematics and open chain architecture. Due to the fact that there is only one attachment module supporting the inchworm robot during crawling, we apply an Unsymmetrical Phase Method (UPM) to realize a stable crawling gait for it. A pine caterpillar robot is derived from combining two inchworm robots together. The crawling gait of it features a repetitive changing chain: Open-Closed-Open. Besides the UPM in open chain states, a four-links kinematic model is applied to control the corresponding joints to transfer the crawling wave along the robot body in the closed chain state. These two prototypes are all constructed and, and their crawling locomotion abilities have been tested on vertical glasses respectively.

Keywords: Biologically-Inspired Robots, Aerial Robotics
Abstract: Optical flow sensing techniques are promising for obstacle avoidance, distance regulation, and moving target tracking, particularly for small mobile robots with limited power and payload constraints. Most optical flow sensing experimental work has been done on mobile platforms which are relatively steady in rotation, unlike the pitching motion expected on flapping wing flyers. In order to assess the feasibility of using optical flow to control an indoor flapping flyer, an 7 gram commercially available ornithopter airframe was equipped with on-board camera and CPU module with mass of 2.5 grams and 2.6 gram battery. An experiment was conducted capturing optical flow information during flapping and gliding flight on the same platform. As expected, flapping introduced substantial systematic bias to the direction estimates to the point of flipping the true direction periodically. Nonetheless, since the optical flow results oscillated at the same frequency as the flapping wings, it is envisioned that one could disambiguate the jittering optic flow measurements by correlating these with real-time feedback from the motor current.

Keywords: Biologically-Inspired Robots, Autonomous Agents, Learning and Adaptive Systems
Abstract: We investigate the problem of a robot maximizing its long-term average rate of return on work. We present a means to obtain an estimate of the instantaneous rate of return when work is rewarded in discrete atoms, and a method that uses this to recursively maximize the long-term average return when work is available in localized patches, each with locally diminishing returns. We examine a puck-foraging scenario, and test our method in simulation under a variety of conditions. However, the analysis and approach applies to the general case.

Keywords: Biologically-Inspired Robots, Space Robotics, Mining Robotics
Abstract: Abstract—Successful long-term settlements on the Moon will need a supply of resources such as oxygen and water, yet the process of regularly transporting these resources from Earth would be prohibitively costly and dangerous. One alternative would be an approach using heterogeneous, autonomous robotic teams, which could collect and extract these resources from the surrounding environment (In-Situ Resource Utilization). The Whegs™ robotic platform, with its demonstrated capability to negotiate obstacles and traverse irregular terrain, is a good candidate for a lunar rover concept. In this research, Lunar Whegs™ is constructed as a proof-of concept rover that would be able to navigate the surface of the moon, collect a quantity of regolith, and transport it back to a central processing station. The robot incorporates an actuated scoop, specialized feet for locomotion on loose substrates, Light Detection and Ranging (LIDAR) obstacle sensing and avoidance, and sealing and durability features for operation in an abrasive environment.

Keywords: Motion Control, Adaptive Control, Path Planning for Multiple Mobile Robot Systems
Abstract: In the lion and man game, a lion tries to capture a man who is as fast as the lion. We study a new version of this game which takes place in a Euclidean environment with a circular obstacle. We present a complete characterization of the game: for each player, we derive necessary and sufficient conditions for winning the game. Their (continuous time) strategies are constructed using techniques from differential games and arguments from geometry. Our main result is a decision algorithm which takes arbitrary initial positions as input, declares one of the players as the winner of the game and outputs a winning strategy for that player. We extend our approach to explicitly construct, in closed form, the decision boundary that partitions the arena into win and lose regions.

Keywords: Motion Control, Virtual Reality and Interfaces
Abstract: The CyberWalk is a large size 2D omni-directional platform that allows unconstrained locomotion possibilities to a walking user for VR exploration. In this paper we present the motion control design for the platform, which has been developed within the homonymous European research project. The objective is to compensate the intentional motion of the user, so as to keep her/him always close to the platform center while limiting the perceptual effects due to actuation commands. The controller acts at the acceleration level, using suitable observers to estimate the unmeasurable intentional walker's velocity and acceleration. A moving reference position is used to limit the accelerations felt by the user in critical transients, e.g., when the walker suddenly stops motion. Experimental results are reported that show the benefit of designing separate control gains in the two orthogonal directions (lateral and sagittal) of a frame attached to the walker.

Keywords: Adaptive Control, Biologically-Inspired Robots, Learning and Adaptive Systems
Abstract: Abstract— In this paper, a Brain Limbic System (BLS) based control algorithm is used to address the problem of target tracking in mobile robotics. The mathematical description of this approach in the form of BELBIC (Brain Emotional Learning Control; also referred to as BLS) is presented and used to generate appropriate velocity profile for the mobile robot to track its target. The overall performance of the system is enhanced via fuzzy clustering of the error and velocity pairs. It is shown that the proposed approach is effective in single and multiple, sequential target tracking tasks.

Keywords: Adaptive Control, Agent-Based Systems, Learning and Adaptive Systems
Abstract: In this paper, adaptive control is investigated for a class of discrete-time nonlinear multi-agent systems (MAS). Each agent is of uncertain dynamics and is affected by other agents in its neighborhood. An agent is able to sense the outputs of the agents inside its neighborhood but is unable to sense those outside its neighborhood. Among all the agents, there is a hidden leader, which knows the desired tracking trajectory, but it is affected by and can only affect those agents inside its neighborhood while all other agents are not aware of its leadership. The decentralized adaptive control is designed for each agent by using the information of its neighbors. Under the proposed decentralized adaptive controls, both rigid mathematical proof and simulation studies are provided to show that all the agents are guaranteed to reach their common goal, i.e., following the desired reference.

Keywords: Motion Control, Nonholonomic Motion Planning, Navigation
Abstract: In the paper, we study the motion planning problem of a mobile robot in the plane. The goal is to design output feedback control such that the resulting path of a mobile robot satisfies desired linear temporal logic (LTL) specifications. Our control strategy is divided into a local output feedback control problem and a supervisory control for LTL specifications. For the former one, we design output feedback control laws to ensure that output trajectories either remain in a simplex, or leave the simplex and enter an adjacent simplex in finite time. For the latter, we construct a transition system based on reachability and search for feasible paths that satisfy the LTL specifications. In this way, a piecewise affine output feedback control is obtained to solve the motion planning problem. A simulation result is presented to illustrate our approach.

Keywords: Path Planning for Manipulators, Mapping, Range Sensing
Abstract: This paper presents a novel method for sensor-based exploration of unknown environments by a general robotic system equipped with multiple sensors. The method is based on the incremental generation of a configuration-space data structure called Sensor-based Exploration Tree (SET). The expansion of the SET is driven by information at the world level, where the perception process takes place. In particular, the frontiers of the explored region efficiently guide the search for informative view configurations. Different exploration strategies may be obtained by instantiating the general SET method with different sampling techniques. Two such strategies are presented and compared by simulations in non-trivial 2D and 3D worlds. A completeness analysis of SET is given in the paper.

Keywords: Path Planning for Manipulators, Visual Servoing
Abstract: This paper presents a motion planning algorithm for industrial manipulators with the simultaneous constraints of avoiding collisions and avoiding the occlusion of specified pixellated regions of an eye-to-hand camera. The system uses a probabilistic roadmap to satisfy the constraints imposed by the command interface of typical industrial manipulators and uses dynamic collision checking to ensure collision-free motion. In the context of a task monitored by a camera, we enhance a probabilistic roadmap with a dynamic occlusion checking algorithm that is able to determine which pixels of the camera are occluded by the robot during each motion segment. The occlusion algorithm is formulated as collision algorithm where the field of view of the camera is represented as a quadtree of frustums. The proposed algorithm is demonstrated in industrial bin picking simulations where the gripper must not occlude the targeted object throughout the task.

Keywords: Path Planning for Manipulators, Medical Robots and Systems
Abstract: This paper discusses the extension of sample-based planning methods to the application of sensor planning for a partially unknown, moving target. This is achieved by modeling the target as a time-varying stochastic process with known mean and variance. Using the unscented transform, the target’s statistics are then propagated through a user-supplied sensing effectiveness metric. The planner is demonstrated for a dynamic X-ray imaging platform tasked with viewing the human knee-joint center during normal, over-ground walking.

Keywords: Path Planning for Multiple Mobile Robot Systems, Sensor Networks
Abstract: When sensors in wireless sensor networks fail or become energy-exhausted, redundant mobile sensors might be moved to cover the sensing holes created by the failed sensors. Within rugged terrains where wheeled sensors are unsuitable, other types of mobile sensors, such as hopping sensors, are needed. In this paper, we address the problem of relocating hopping sensors to the sensing holes. Recent study for this problem considered moving sensors along the shortest path. The shortest path might be used repeatedly and therefore create other sensing holes. In order to overcome these weaknesses, we propose multipath-based schemes considering the balanced assignment for the relocation of hopping sensors. Simulation results show that the proposed schemes guarantee a more balanced migration distribution of efficient sensors and a higher movement success ratio of required sensors than those of the shortest path-based schemes.

Keywords: Motion Control, Wheeled Robots, Sensor Fusion
Abstract: This paper treats a trajectory tracking control of a mobile robot by a single CCD camera and range sensors. First, the mobile robot detects the obstacle based on information of both the image and the distance. And then, from the obstacle information, the mobile robot generates a trajectory to avoid the obstacle. Finally, the usefulness of our proposed methods is demonstrated through experiment.

Keywords: Telerobotics, Control Architectures and Programming
Abstract: Teleoperation has a long history in the robotics community and numerous haptic teleoperation systems employing manipulators have been proposed in the literature. On the one hand, systems have been designed which employ commercial hardware and hence generally suffer from low update rates and high delays due to restrictions of commercial manipulator controllers and haptic device controllers. On the other hand, haptic teleoperation systems designed by research institutions often provide only few degrees of freedom. Our 6DoF haptic teleoperation system, however, combines the amenities of commercial hardware with a high performance distributed control architecture which enables us to achieve update rates of more than 2kHz and delays in the range of only 100us. This paper focuses on the architecture of our system and demonstrates how to achieve this performance using commercial hardware. Moreover, we show why update rates of more than 1kHz are essential for certain teleoperation tasks. Especially with high approach velocities and stiff environments, high update rates and low delays are key requirements for stability and thus for realistic haptic perception. We present experimental results demonstrating the influence of the update rate on system stability. These results not only highlight the benefits of high update rates but also give hints on how to estimate the update rate necessary to achieve stable teleoperation for a given environment stiffness.

Keywords: Telerobotics, Haptics and Haptic Interfaces
Abstract: Kinematically redundant robotic manipulators (KRRM) can provide a great degree of flexibility for working in complex unstructured environments. Teleoperation control of KRRM requires a strategy to resolve the redundancy of the slave robot while achieving transparency in the task space. In this paper, a two-master control approach is proposed in which the first master transparently controls the redundant slave end-effector in the task space, denoted as the primary task. Meanwhile, a second master exploits the slave redundancy to perform a secondary task such as obstacle avoidance or internal position control. Kinematic redundancy is considered for the slave robot and the traditional autonomous null-space control approach is also accommodated. Teleoperation control is achieved in two steps. First, velocity-level redundancy resolution is attained through new joint-space Lyapunov-based adaptive motion/force controllers. Coordinating reference commands for the joint-space controllers are designed to give priority to the primary task and decoupling between the tasks is achieved without the use of a dynamically consistent pseudo-inverse. Experimental results with two identical planar two-degree-of-freedom master devices controlling a simulated four-degree-of-freedom redundant slave robot show the effectiveness of the approach.

Keywords: Telerobotics
Abstract: Traditional bilateral teleoperation communicates both motion and force information explicitly between master and slave devices. Any such closed loop architecture trades off performance with potential instability, especially when using force measurements of high inertia slaves contacting stiff environments. More conservatively, open-loop architectures avoid stability issues, transmitting motion commands while allowing any force feedback only via sensory substitution. We propose open-loop bilateral teleoperation as an alternative communicating force information explicitly and restricting motion information to visual feedback. This naturally matches a user's needs, seeing motion and feeling forces. A user study was conducted to compare the novel user interface to three common open loop and bilateral control methods: position control, position control with force feedback, and rate control. The results of this study show that users are able to achieve superior force tracking with little tremor. Position tracking and trial completion time suffered from the lack of direct position connection, but training provides a promising method to restore this performance.

Keywords: Telerobotics, Haptics and Haptic Interfaces, Networked Robots
Abstract: Results of experimental studies of a teleoperator system with projection-based force reflection algorithms in the presence of communication constraints are presented. It is demonstrated that, using the projection-based force reflection algorithms, the admissible force reflection gain can be substantially increased without loosing the overall stability, which confirms the earlier theoretical results. It is also shown that this improvement is achieved without transparency deterioration.

Keywords: Telerobotics, Force and Tactile Sensing
Abstract: In bilateral teleoperation, the operator experiences forces and torques applied to the slave manipulator. These forces and torques, however, consist of two components: on the one hand, forces and torques due to environmental contact, and on the other hand, non-contact forces, i.e., inertial forces, centrifugal forces, Coriolis forces, and associated torques. For several reasons, eliminating these non-contact forces and torques from the force-torque measurements of the slave or scaling them can be advantageous. For instance, in highly dynamic teleoperation tasks, these forces and torques may contribute to operator fatigue or hamper the detection of environmental contacts. This paper briefly reviews the estimation of inertial parameters of the slave load, e.g., an end-effector or a gripper. Subsequently, a method for eliminating the non-contact forces and torques from the measurements of a wrist-mounted force-torque sensor or scaling them is presented. After a brief overview of our teleoperation system, experimental results are presented which demonstrate the effectiveness of our approach.

Keywords: Mechanism Design, Service Robots, Physical Human-Robot Interaction
Abstract: Service robots are anticipated to be used in unstructured areas such as homes, hospitals, and public areas in the near future. However, safety issues need to be addressed before this can occur. In particular, robot manipulators that handle objects by physical contact run the risk of colliding with people or objects. Thus, it is important to prevent collisions that could injure people and damage robot manipulators. In this study, a safe joint mechanism is developed to ensure the safe use of a manipulator. This mechanism, termed ‘Spring-Clutch,’ is a simple passive mechanism that consists of a coil spring and a CAM mechanism. When a torque is applied that is less than a threshold value, Spring-Clutch functions as a rigid joint between the input and the output. However, when an applied torque exceeds the threshold, angular displacement occurs between the input and output to reduce the collision force. If the applied torque is removed, Spring-Clutch immediately returns to its nominal position without the need for additional operations. This paper describes the design principles and performance of Spring-Clutch, and discusses the possibility of its practical use as a joint mechanism for safe manipulation.

Keywords: Mechanism Design, Motion Control, Visual Servoing
Abstract: Spherical joints have evolved into a critical component of many robotic systems, often used to provide dexterity at the wrist of a manipulator. In this work, a novel 3 degree of freedom spherical joint is proposed, actuated by tendons that run along the surface of the sphere. The joint is mechanically simple and avoids mechanical singularities. The kinematics and mechanics of the joint are modeled and used to develop both open and closed loop control systems. Simulated and experimental assessment of the joint performance demonstrates that it can be successfully controlled in 3 degrees of freedom. It is expected that the joint will be a useful option in the development of emerging robotic applications, particularly those requiring miniaturization.

Keywords: Mechanism Design, Parallel Robots, Humanoid Robots
Abstract: This paper develops a 3-DOF active rotational ball joint with a simple and compact mechanism, which can realize a rotation around an any-direction rotational axis with a well manipulability and can change its direction of rotational axis smoothly and arbitrarily when it is on rotating. The mechanism principle of this joint is proposed and analyzed. Then the ball joint is developed with good dynamics and lower friction and experimental verification on the proposed mechanism is performed. The effectiveness of the mechanism principle is outlined by some experimental results.

Keywords: Mechanism Design, Parallel Robots
Abstract: This paper presents the design optimization of a Delta-like robot manipulator with respect to multiple global stiffness objectives. For this purpose, a systematic elasto-geometrical modeling method is used to derive the analytical manipulator stiffness models by taking into account their link and joint compliances. The models are then involved within a statistically sensitivity analysis of the influence of the geometric parameters on four global indices that describe the structure stiffness over the workspace. Multi-Objective Genetic Algorithm, i.e. Pareto-optimization, is taken as the appropriate framework for the definition and the solution of the addressed multi-objective optimization problem. Our approach is original in the sense that it is systematic and it can be applied to any serial and parallel manipulators for which stiffness is a critical issue.

Keywords: Mechanism Design, Parallel Robots, Kinematics
Abstract: Less degree-of-freedom robots are useful for special applications. Specifically, practical application of 4-DOF parallel mechanism has been rare, though synthesis on this type has been conducted quite a few. Recently, we proposed a revolute joint-based 3T1R 4-DOF parallel mechanism having Schonflies motions whose output rotational motion is a roll motion. This work proposes another type of a new 3T1R 4-DOF parallel mechanism having Schonflies motions whose rotational motion is a pitch motion. The position analysis and kinematic modeling for the mechanism are performed, and its workspace size and kinematic characteristic with respect to the kinematic isotropic characteristic are examined. To support high potential of the mechanism for real applications, three different versions are suggested and each motion capability is verified through its simulator. Finally, a prototype is developed to verity its actual motion capability.

Keywords: Computer Vision, Aerial Robotics
Abstract: Miniature Aerial Vehicles (MAVs) are quickly gaining acceptance as a platform for performing remote sensing or surveillance of remote areas. However, because MAVs are typically flown close to the ground (1000 feet or less in altitude), their field of view for any one image is relatively small. In addition, the context of the video (where and at what orientation are the objects being observed, the relationship between images) is unclear from any one image. To overcome these problems, we propose a geo-referenced mosaicing method that creates a mosaic from the captured images and geo-references the mosaic using information from the MAV IMU/GPS unit. Our method utilizes bundle adjustment within a constrained optimization framework. Using real MAV video, we have demonstrated our mosaic creation process on over 400 frames. The results mosaic was geo-referenced with less than 7m of error.

Keywords: Contact Modelling, Animation and Simulation
Abstract: This paper presents a method to utilize a portbased multibody contact model for simulating dynamic interaction between irregular surfaces. The existing compliant contact model requires an analytic parametrization of the surfaces involved in the interaction, the definition of a Gauss frame in each of the contact points and initialization of the candidate contact points. The authors intend to apply this contact model for cases in which the surfaces of the 3D interacting bodies can not be described (easily) by a geometrically defined surface. Such surfaces are often represented by 3D point meshes. This implies that the surfaces of the bodies have to be reconstructed from 3D point meshes where initialization of the candidate contact points is not arbitrary. This paper proposes the reconstruction of such surfaces by means of polynomial interpolation. With the aim of having a computationally efficient simulator, the surface interpolation is restricted to small patches around the candidate contact points. To select these candidates, the proposed simulation approach is completed by using a fast (existing) collision detection algorithm. Simulation results are validating the effectiveness of the proposed modeling and simulation approach.

Keywords: Computer Vision, Range Sensing, Domestic Robots
Abstract: A novel and inexpensive mechanism for acquiring 3D data suitable for indoor mobile robots is introduced. The scanner is currently capable of ranging up to 4m with an accuracy of 0.05m and costs less than 500USD. The scans cover the whole 360 degrees around the robot at heights from floor level to 1m. The data so obtained is particularly applicable to navigation, mapping and obstacle avoidance. The scanner consists of a webcam, visual encoder disk, angled laser line projector and determines range based on triangulation. The scan rate depends upon the frame rate of the camera and its rotation speed.

Keywords: Computer Vision, Mapping, Aerial Robotics
Abstract: Mapping the environment is necessary for navigation in unknown areas with autonomous vehicles. In this context, a method to process depth images for occupancy grid mapping is developed. Input data are images with pixel-based distance information and the corresponding camera poses. A measurement model, focusing on stereo-based depth images and their characteristics, is presented. Since an enormous amount of range data must be processed, improvements like image pyramids are used so that the image analysis is possible in real-time. Output is a grid-based image interpretation for sensor fusion, i.e. a world-centric occupancy probability array containing information stored in a single image. Different approaches to draw pixel information into a grid map are presented and discussed in terms of accuracy and performance. As a final result, 3D occupancy grids from aerial image sequences are presented.

Keywords: Computer Vision
Abstract: This paper presents an architecture extending bottom-up visual attention for dynamic scene analysis. In dynamic scenes, particularly when learning actions from demonstrations, robots have to stably focus on the relevant movement by disregarding surrounding noises, but still maintain sensitivity to a new relevant movement, which might occur in the surroundings. In order to meet the contradictory requirements of stability and sensitivity for attention, this paper introduces biologically-inspired mechanisms for retinal filtering and stochastic attention selection. The former reduces the complexity of peripheral signals by filtering an input image. It results in enhancing bottom-up saliency in the fovea as well as in detecting only prominent signals from the periphery. The latter allows robots to shift attention to a less but still salient location in the periphery, which is likely relevant to the demonstrated action. Integrating these mechanisms with computation for bottom-up saliency enables robots to extract important action sequences from task demonstrations. Experiments with a simulated and a natural scene show better performance of the proposed model than comparative models.

Keywords: Computer Vision, Dynamics, Calibration and Identification
Abstract: Vision can be used as a sensor for measuring the position of a visual marker. When the displacement of the marker over the camera exposure time is significant, the obtained position measurement is an image of the trajectory over the exposure time. This paper deals with dynamical models providing a prediction of the measurement from the continuous-time trajectory. The first contribution of the paper consists in the development of models for the global shutter and rolling shutter modes with variable exposure time. The second contribution consists in a methodology for the validation of these models. This methodology is used for validating the model of a camera with global shutter mode with full exposure time.

Keywords: Visual Servoing
Abstract: The purpose of this paper is to show what visual prediction can bring to Image-Based Visual Servoing (IBVS). The visual feature prediction is obtained thanks to the interaction matrix. Based on a Nonlinear Model Predictive Control (NMPC) strategy, the visual servoing task is formulated into an optimization problem. The error between the reference features and the predicted features is to be minimized over a receding prediction horizon. Numerous simulations highlight the interest of prediction, especially for difficult configurations such as large motion and rotation.

Keywords: Computer Vision, Localization, Navigation
Abstract: In this paper we present a novel approach to perform indoor self-localization using reference omnidirectional images. We only need one omnidirectional image of the whole scene stored in the robot memory and a conventional on board camera. We match the omnidirectional image and the conventional images captured by the on board camera and compute the hybrid epipolar geometry using lifted coordinates and robust techniques. We map the epipole in the reference omnidirectional image to a ground plane through a homography in lifted coordinates also, giving the position of the robot in the planar ground, and its uncertainty. We perform experiments with simulated and real data to show the feasibility of this new self-localization approach.

Keywords: Computer Vision, Intelligent Vehicles, Sensor Fusion
Abstract: Locating all obstacles around a moving robot and classifying them as stable obstacles or not by a sensor such as an omnidirectional camera are essential for the robot's smooth movement and avoiding problems in synchronizing many sensors. However, there are few works on locating and classifying all obstacles around a robot while it is moving by only one omnidirectional camera. In order to locate obstacles, we regard floor boundary points where robots can measure the distance from the robot by one omnidirectional camera as obstacles. Tracking them, we can classify obstacles by comparing the movement of each tracked point with odometry data. Moreover, our method changes a threshold to detect the points based on the result of comparing in order to enhance classification. The classification ratio of our method is 85.0%, which is four times higher than that of a method without changing a parameter to detect the points.

Keywords: Computer Vision, Visual Tracking
Abstract: Robot vision has a lot to win as well with wide field of view induced by catadioptric cameras as with redundancy brought by stereovision. Merging these two characteristics in a single sensor is obtained by combining a single camera and multiple mirrors. This paper proposes a 3D model tracking algorithm that allows a robust tracking of 3D objects using stereo catadioptric images given by this sensor. The presented work relies on an adapted virtual visual servoing approach, a non-linear pose computation technique. The model take into account central projection and multiple mirrors. Results show robustness in illumination changes, mistracking and even higher robustness with four mirrors than with two.

Keywords: Grasping, Underactuated Robots, Contact Modelling
Abstract: Highly underactuated and passively adaptive robotic hands have shown great promise for robust performance in unstructured settings. In order to fully realize this potential, efficient tools are needed to analyze the execution of a grasp when using this class of devices. Along this line, this paper introduces a quasistatic analysis method for underactuated hands. First, we predict whether initial contacts between the fingers and the object are stable throughout the execution of a grasp, or the fingers will slip as the hand closes. Second, we compute the unbalanced forces applied to the object during the grasping process. Finally, once the grasp is complete, we analyze its stability as actuator forces are increased. These computations are performed in 3D, allow arbitrary kinematic structure of the fingers or geometry of the target object and take into account frictional constraints. We discuss applications of this method focusing on both on-line computation to execute a specific grasping task and off-line optimization to increase the range of grasps that can be performed using a given hand model.

Keywords: Learning and Adaptive Systems, Manipulation Planning, AI Reasoning Methods
Abstract: Since humanoid robots have similar body structures to humans, a humanoid robot is expected to perform various dynamic tasks including object manipulation. This research focuses on issues related to learning and performing object manipulation. Basic motion primitives for tasks are learned from observation of human’s behaviors. An object manipulation task is divided into two types of motion primitives, which are represented as hidden Markov models (HMMs): one for a body motion primitive and the other for the relation between the object and body parts, which manipulate the object. When performing a task, a natural whole body motion is associated from an object motion by using learned motion primitives. Furthermore, the associated body motion is reshaped in both spatial and temporal space, in a more precise way. The reshaping in spatial space is realized in two stages by a feedback control policy learned with reinforcement learning and by constrained inverse kinematics. Key features like endeffectors for manipulation and timing for a task are extracted and used for the feedback control policy learning. The reshaping in temporal space is realized by comparing a predicted and observed object motion speed.

Keywords: Entertainment Robotics, Manipulation Planning, Visual Tracking
Abstract: This paper describes our successful implementation of a robot that autonomously and strategically removes multiple blocks from an unstable Jenga tower. We present an integrated strategy for perception, planning and control that achieves repeatable performance in this challenging physical domain. In contrast to previous implementations, we rely only on low-cost, readily available system components and use strategic algorithms to resolve system uncertainty. We present a three-stage planner for block extraction which considers block selection, extraction order, and physics-based simulation that evaluates removability. Existing vision techniques are combined in a novel sequence for the identification and tracking of blocks within the tower. Discussion of our approach is presented following experimental results on a 5-DOF robot manipulator.

Keywords: Autonomous Agents, AI Reasoning Methods, Recognition
Abstract: Autonomous systems situated in the real world often need to recognize, track, and reason about various types of physical objects. In order to allow reasoning at a symbolic level, one must create and continuously maintain a correlation between symbols labeling physical objects and the sensor data being collected about them, a process called anchoring.

In this paper we present a stream-based hierarchical anchoring framework extending the DyKnow knowledge processing middleware. A classification hierarchy is associated with expressive conditions for hypothesizing the type and identity of an object given streams of temporally tagged sensor data. The anchoring process constructs and maintains a set of object linkage structures representing the best possible hypotheses at any time. Each hypothesis can be incrementally generalized or narrowed down as new sensor data arrives. Symbols can be associated with an object at any level of classification, permitting symbolic reasoning on different levels of abstraction. The approach has been applied to a traffic monitoring application where a UAV collects information about a small urban area in order to detect traffic violations.

Keywords: Field Robots, Calibration and Identification
Abstract: We propose in this paper an improved geometric formulation of POE (Product Of Exponential) based kinematic calibration of serial robots, which is based on the work of [1]. We use both joint offset-free formulation and adjoint transformation errors of joint screws, and apply it to the calibration of an elbow manipulator. Our formulation explains why the original POE calibration always fails with the existence of joint offset errors; the adjoint formulation of joint screw errors eliminates joint screw constraints that was imposed in the original iterated least square calibration algorithm. The second contribution of this paper is the proposal of a modified POE formulation which adopts point measurement data instead of frame measurement data of the end-effector, which can be more realistic and convenient for practical implementation. Simulation results show that the proposed method is plausible and effective. An experiment is under preparation to verify the effectiveness of the proposed calibration method on an elbow manipulator built by Googol Technology.

Keywords: Cellular and Modular Robots, Programming Environment
Abstract: LDP (Locally Distributed Predicates) is a distributed, high-level language for programming modular reconfigurable robot systems (MRRs). In this paper we present the implementation of two motion-planning algorithms in LDP, and analyze both their performance and ease of implementation. We present multiple variations of one planner, including a novel resource allocation algorithm. We then draw conclusions about both the utility of the motion-planning algorithms and the suitability of LDP to the problem space. Our experiments suggest that the additional generality and separation of-concerns offered by metamodule-based planning approaches do have a cost in time and/or energy terms, but that that cost may be worth paying, depending upon the goals of the overall system and the details of the underlying modules.

Keywords: Cellular and Modular Robots
Abstract: To understand the capabilities and behavior of a robot it is important to have knowledge about its physical structure and how its actuators control its shape. In this paper we analyze the kinematics and develop a general representation of a configuration of the heterogeneous modular robot Odin. The basics of estimating the shape of the Odin robot is presented, which leads the way for further research on the Odin robot and similar robots. We present an example of how to represent and estimate the shape of a tetrahedron configuration with various types of modules. We conclude that this representation can be used to find the physical constraints of the Odin robot and estimate the shape of a configuration.

Keywords: Cellular and Modular Robots, Medical Robots and Systems, Distributed Robot Systems
Abstract: Self-assembly is a process in which individual components form an organized structure as a consequence of local interactions. When using magnetics to create interaction forces, the magnetic flux distribution of a self-assembling system changes as its assembly state varies. Since Hall effect sensors are a convenient and effective means to detect changes in the magnetic field, we explore their applicability to monitoring the morphology of such magnetically self-assembling systems. We find that optimal positions for the sensor can be found where the flux changes maximally. Our analysis is applied to two different systems by deriving the flux changes for all possible states, and theoretical flux changes are verified with experiments. In addition, we show that a small number of sensors is sufficient for robust state determination. In addition to state detection, experiments show the potential for angle measurement for compliant cylindrical magnet joints using a single Hall sensor.

Keywords: Cellular and Modular Robots
Abstract: Modular, self-reconfigurable robots are robots that can change their own shape by physically rearranging the modules from which they are built. Self-reconfiguration can be controlled by e.g. an off-line planner, but numerous implementation issues hamper the actual self-reconfiguration process: the continuous evolution of the communication topology increases the risk of communications failure, generating code that correctly controls the self-reconfiguration process is non-trivial, and hand-tuning the self-reconfiguration process is tedious and error-prone.

To address these issues, we have developed a distributed scripting language that controls self-reconfiguration of the ATRON robot using a robust communication scheme that relies on local broadcast of shared state. This language can be used as the target of a planner, offers direct support for parallelization of independent operations while maintaining correct sequentiality of dependent operations, and compiles to a robust and efficient implementation. Moreover, a novel feature of this language is its reversibility: once a self-reconfiguration sequence is described the reverse sequence is automatically available to the programmer, significantly reducing the amount of work needed to deploy self-reconfiguration in larger scenarios. We demonstrate our approach with long-running (reversible) self-reconfiguration experiments using the ATRON robot and a reversible self-reconfiguration experiment using simulated MTRAN modules.

Keywords: Cellular and Modular Robots
Abstract: In our previous works we had developed a framework for self-reconfiguration planning based on graph signature and graph edit-distance. The graph signature is a fast isomorphism test between different configurations and the graph edit-distance is a similarity metric. But the algorithm is not suitable for modules with symmetry. In this paper we improve the algorithm in order to deal with symmetric modules. Also, we present a new heuristic function to guide the search strategy by penalizing the solutions with more number of actions. The simulation results show the new algorithm not only deals with symmetric modules successfully but also finds better solutions in a shorter time.

Keywords: Aerial Robotics, Adaptive Control, Visual Servoing
Abstract: This paper presents a novel adaptive controller for image-based visual servoing of a small autonomous helicopter to cope with uncalibrated camera parameters and unknown 3-D geometry of the feature points. The controller is based on the backstepping technique but differs from the existing backstepping-based methods because the controller maps the image errors onto the actuator space via a depth-independent interaction matrix to avoid estimation the depths of the feature points. The new design method makes it possible to linearly parameterize the closed-loop dynamics by the unknown camera parameters and coordinates of the feature points in the three dimensional space so that an adaptive algorithm can be developed to estimate the unknown parameters and coordinates on-line. Two potential functions are introduced in the controller to guarantee convergence of the image errors and to avoid trivial solutions of the estimated parameters. The Lyapunov method is used to prove the asymptotic stability of the proposed controller based on the nonlinear dynamics of the helicopter. Simulations have been also conducted to demonstrate the performance of the proposed method.

Keywords: Aerial Robotics, Computer Vision
Abstract: We consider the problem of autonomously flying a helicopter in indoor environments. Navigation in indoor settings poses two major challenges. First, real-time perception and response is crucial because of the high presence of obstacles. Second, the limited free space in such a setting places severe restrictions on the size of the aerial vehicle, resulting in a frugal payload budget.

We autonomously fly a miniature RC helicopter in small known environments using an on-board light-weight camera as the only sensor. We use an algorithm that combines data-driven image classification with optical flow techniques on the images captured by the camera to achieve real-time 3D localization and navigation. We perform successful autonomous test flights along trajectories in two different indoor settings. Our results demonstrate that our method is capable of autonomous flight even in narrow indoor spaces with sharp corners.

Keywords: Aerial Robotics, Navigation
Abstract: This paper presents a vision-based navigation strategy for a Vertical Take-off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) using a single embedded camera observing natural landmarks. In the proposed approach, images of the environment are first sampled and stored as a set of ordered key images (visual path) and organized providing a visual memory of the environment. The robot navigation task is then defined as a concatenation of visual path subsets (called visual route) linking the current observed image and a target image belonging to the visual memory. The UAV is controlled to reach each image of the visual route using a vision-based control law adapted to its dynamic model and without explicitly planning any trajectory. This framework is largely substantiated by experiments with a X4-flyer equipped with a fisheye camera.

Keywords: Aerial Robotics, Visual Servoing, Search and Rescue Robots
Abstract: This paper describes an object tracking system using an autonomous Micro Air Vehicle (MAV) and demonstrate its potential use for civilian purposes. The vision-based control system relies on a color and feature based vision algorithm for target detection and tracking, Kalman filters for relative pose estimation, and a nonlinear controller for MAV stabilization and guidance. The vision algorithm relies on information from a single onboard camera. An arbitrary target can be selected in real-time from the ground control station, thereby outperforming template and learning-based approaches. Experimental results obtained from outdoor flight tests, showed that the vision-control system enabled the MAV to track and hover above the target as long as the battery is available.

Keywords: Aerial Robotics, Computer Vision, Surveillance Systems
Abstract: We propose a robust and accurate method for multi-target geo-localization from airborne video. The difference between our approach and other approaches in the literature is fourfold: 1) it does not require gimbal control of the camera or any particular path planning control for the UAV; 2) it can instantaneously geo-locate multiple targets even if they were not previously observed by the camera; 3) it does not require a georeferenced terrain database nor an altimeter for estimating the UAV’s and the target’s altitudes; and 4) it requires only one camera, but it employs a multi-stereo technique using the image sequence for increased accuracy in target geo-location. The only requirements for our approach are: that the intrinsic parameters of the camera be known; that the on board camera be equipped with global positioning system (GPS) and inertial measurement unit (IMU); and that enough feature points can be extracted from the surroundings of the target. Since the first two constraints are easily satisfied, the only real requirement is regarding the feature points. However, as we explain later, this last constraint can also be alleviated if the ground is approximately planar. The result is a method that can reach a few meters of accuracy for an UAV flying at a few hundred meters above the ground. Such performance is demonstrated by computer simulation, in-scale data using a model city, and real airborne video with ground truth.

Keywords: Cooperating Robots, Networked Robots, Cooperative Manipulators
Abstract: In this paper we consider cooperative manipulation problems where a large group (swarm) of non-articulated mobile robots is trying to cooperatively control the velocity of some larger rigid body by exerting forces around its perimeter. We consider a second-order dynamic model for the object but use a simplified contact model. We seek solutions that require minimal information sharing among the swarm members. We present a velocity control law that is asymptotically stable. In the case of a constant desired velocity, it is shown that no coordination is required between the swarm members. For more complex trajectories we introduce a decentralized feed-forward component that uses an online consensus estimate of the swarm's configuration. The results are illustrated in simulation.

Keywords: Cooperative Manipulators, Cooperating Robots, Force Control
Abstract: A direct teaching system emphasizing safety and perability for SP02, an upper-body humanoid that cooperates with a human in a cell-production workspace has been described. The system has a direct teaching device, which enables an operator to teach a multi-D.O.F manipulator at comfortable posture despite large changes in the pose of an end-effector. The double-checked safety-related part(SRP/CS) introducing a safety module satisfies the safety performance defined by the international safety standard. To improve the operability of an operator, impedance parameters in a variable impedance control are set through several direct teaching experiments. Through a simple direct teaching experiment, the safety performance of the SRP/CS and the teaching performance of the direct teaching system was successfully confirmed.