Keywords: Range Sensing
Abstract: In this paper we present a framework for 3D geometric shape segmentation for close-range scenes used in mobile manipulation and grasping, out of sensed point cloud data. Our proposed approach proposes a robust geometric mapping pipeline for large input datasets that extracts relevant objects useful for a personal robotic assistant to perform manipulation tasks. The objects are segmented out from partial views and a reconstructed model is computed by fitting geometric primitive classes such as planes, spheres, cylinders, and cones. The geometric shape coefficients are then used to reconstruct missing data and fill holes. Residual points are resampled and triangulated, to create smooth decoupled surfaces that can be manipulated. The resulted map is represented as a hybrid concept and is comprised of 3D shape coefficients and triangular meshes used for collision avoidance in manipulation routines.

Keywords: Range Sensing, Recognition
Abstract: In this paper we present a new approach for labeling 3D points with different geometric surface primitives using a novel feature descriptor -- the Fast Point Feature Histograms, and discriminative graphical models. To build informative and robust 3D feature point representations, our descriptors encode the underlying surface geometry around a point p using multi-value histograms. This highly dimensional feature space copes well with noisy sensor data and is not dependent on pose or sampling density. By defining classes of 3D geometric surfaces and making use of contextual information using Conditional Random Fields (CRFs), our system is able to successfully segment and label 3D point clouds, based on the type of surfaces the points are lying on. We validate and demonstrate the method's efficiency by comparing it against similar initiatives as well as present results for table setting datasets acquired in indoor environments.

Keywords: Localization, Range Sensing, Navigation
Abstract: The problem of mobile robot self-localization is considered as solved since Thrun’s et. al pioneering work using monte-carlo filters for robot Localization (MCL). However, MCL is robust and precise under constraints like completely known environments and the sensor data must contain enough ”true data” as contained in the map. In fact these conditions cannot always be guaranteed, which may results in a poor accuracy of the localization. In this paper we present a area-based observation model that is applied to MCL self-localization. The model is based on the idea of tracking the ground area inside the ”free space” (not occupied cells) of a known map. Experimental data shows that the proposed model improves the robustness and accuracy of laser and stereo vision sensors under certain conditions like incomplete map, limited FOV and limited range of sensing. We also present an efficient approximation of our sensor model based on integral images.

Keywords: Range Sensing, Computer Vision, Visual Tracking
Abstract: In the context of 3-D scene modeling, this work aims at the accurate estimation of the pose of a close-range 3-D modeling device, in real-time and passively from its own images. This novel development makes it possible to abandon using inconvenient, expensive external positioning systems. The approach comprises an ego-motion algorithm tracking natural, distinctive features, concurrently with customary 3-D modeling of the scene. The use of stereo vision, an inertial measurement unit, and robust cost functions for pose estimation further increases performance. Demonstrations and abundant video material validate the approach.

Keywords: Physical Human-Robot Interaction, Cognitive Human-Robot Interaction
Abstract: The challenge of this work is to study the design and development of human-robot collaboration (HRC) in cellular manufacturing. Based on the concept of human collaborative design, four main design factors are being identified and developed in an active HRC prototype production cell for cable harness assembly. Human collaborative design aims to optimize the system design for the advantage of collaboration between human and robots based on human considerations. Task modeling approach is developed to study and analyze the task in order to identify the collaboration tasks to develop the collaboration planning. In the collaboration safety development, five safety designs, cover both hardware and control design, are proposed and developed in the prototype system. Risk assessment is conducted to verify the safety design. Two main experiments were conducted as preliminary study to investigate mental workload in HRC. A multimodal information support system is developed in the study of man-machine interface in this work to provide a comprehensive human-robot interface to facilitate human operator. The system performance evaluation had proven the improvement of prototype production cell with HRC design for cellular manufacturing.

Keywords: Physical Human-Robot Interaction, Motion Control
Abstract: This paper presents an energy-based control strategy to be used in robotic systems working closely or cooperating with humans. The presented method bounds the dangerous behavior of the robot during the first instants of the impact in which the collision is not yet detected by limiting the energy stored into the system to a maximum imposed value. Two critical physical human robot interaction (pHRI) cases are studied, these are the collision either against a free or a clamped head. Safe energy values that can be used as reference are retrieved analyzing experimental data of energy absorption to failure of cranium bones and cervical spinal cords. The limit energy based control scheme is implemented in a prototype series elastic actuator joint. The model and the control scheme of the system are analysed. The proposed control scheme is a position-based controller that corrects the position trajectory reference in function of the maximum energy value imposed by the user. Preliminary results are presented to show that the unit and the proposed control scheme are capable of limiting the energy to a maximum value imposed.

Keywords: Physical Human-Robot Interaction
Abstract: In this paper, we introduce a passive mobile robot with casters developed based on the concept of passive robotics. This mobile robot consists of two casters with servo brakes, one passive rigid wheel and a controller. We can manipulate the robot by controlling external force/moment applied by a human based on the control of the servo brakes attached to the casters. We consider the characteristics of the servo brakes and control the brake torque of each caster based on the braking force and moment constraint so that several motion functions of the robot are realized based on the applied force. This allows the robot to track a path without using servo motors. The motion control based on the environment information is also realized, so that we could avoid the collision with obstacles. These functions are implemented to the robot experimentally and experimental results illustrate the validity of the robot system and its control method.

Keywords: Animation and Simulation, Physical Human-Robot Interaction, Humanoid Robots
Abstract: It is believed that from this point forward, there will be a need for industrial robots that work alongside and cooperatively with humans. However, the current development of existing robotics technology is inadequate to ensure the safety of such new industrial robots. Our research proposes a safety-planning technology called Coexistence Hazard Avoidance Technology, designed for use with a low-powered human-collaborative industrial robot. We load this technology into a risk-management simulator and verify that by using it, a dynamic planning method for the safe operation of robots can be reasonably undertaken in terms of both theory and calculation.

Keywords: Medical Robots and Systems, Rehabilitation Robotics
Abstract: This paper describes an algorithm to estimate tremor and voluntary motion from measured motion data. Estimation is performed by means of an extended Kalman filter (EKF), which also estimates tremor parameters. Comparison of the proposed method with techniques described in the literature are conducted with two experimental data sets from tremor patients performing the same task, drawing a spiral. The presented algorithm may be directly applied in real-time pathological tremor compensation systems.

Keywords: Haptics and Haptic Interfaces, Telerobotics, Cognitive Human-Robot Interaction
Abstract: This paper proposes a new ergonomic frame to describe the attitude of a robot arm and to be used for human-machine interface in telerobotic with application to tele-sonography. A three part psychophysical analysis enabled us to design this new system of angles exhibiting a good decorrelation among its degrees of freedom. A decorrelation improvement of up to 83% can be noticed compare to the standard 3-1-3 Euler angles. This new frame has been exploited to conceive human-machine interface with a low cost input device such as the standard IT mouse. Psychophysical results show indisputable superiority of our new system compare to the standard Euler one for orientation tracking in teleoperation conditions.

Keywords: Medical Robots and Systems
Abstract: A novel heart surface motion estimation framework for a robotic surgery on a stabilized beating heart is proposed. It includes an approach for the reconstruction and prediction of heart surface motion based on a novel physical model of the intervention area described by a distributed parameter system. Instead of conventional element methods, a meshless method is used for a spatial and temporal decomposition of this system. This leads to a finite-dimensional state-space form. Furthermore, the state of the resulting lumped-parameter system, which provides an approximation of the deflection and velocity of the heart surface, is dynamically estimated under consideration of uncertainties both occurring in the system and arising from noisy camera measurements. By using the estimation results, an accurate reconstruction of heart surface motion for the synchronisation of the surgical instruments is also achieved at occluded or non-measurement points.

Keywords: Medical Robots and Systems, Biomimetics
Abstract: We proposed a fabrication method for multiscale transparent arteriole and capillary vessel models and demonstrated the fabrication of microchannels with circular cross sections Φ10 - 500 um. First, we demonstrated fabrication of Φ10 - 500 um arteriole and capillary vessel block models using photolithography. The circularity of fabricated Φ10, 50, and 500 um microchannels were 84.0%, 61.5%, and 82.3%, respectively. Flow experiments demonstrated that these channels had no leakage. Next, we proposed a fabrication method for Φ100 - 500 um arteriole membrane models, which connect larger membrane models and smaller block models. These models were prepared with grayscale lithography and a wax and PVA (polyvinyl alcohol) mixture material. The proposed approach overcame the brittleness of a previous sacrificial model fabricated by ink jet rapid prototyping. The membrane model had a circular cross section with a channel circularity of 90%. Finally, we succeeded in making transparent membranous and block arteriole model with which we can simulate blood circulation.

Keywords: Legged Robots, Dynamics
Abstract: Abstract—This paper reports some interesting results on our experimental study of parametrically excited dynamic bipedal walking. We describe the details of the walking machine that has telescopic legs, semicircular feet, free hip-joint and counterweights. The walker can sustain stable dynamic walking on level ground based on mechanical energy restoration in accordance with the principle of parametric excitation utilizing the effects of semicircular feet and counterweights. Results of numerical analysis of the effect of the counterweights on the gait efficiency are also described.

Keywords: Animation and Simulation, Virtual Reality and Interfaces, Manipulation Planning
Abstract:

Keywords: Field Robots, Navigation, Localization
Abstract: This paper introduces the design and implement of a novel control systems for power substation equipment inspection robot. According to the real condition of the power substation equipment inspection, the overall structure of the robot control systems are described, and a new monocular robot's navigation method based on colorful image processing was proposed. By the use of image partition of the HSI model and the mathematic morphology, pick out the trajectory and distinguish the stop-sign drew beforehand from the image. Then use "sampling estimated" method to calculate the parameters of navigation. And the industrial operation of the system shows that the control system can form a kind of full monitor system for substation to greatly improve the safety, dependability and reality of the substation inspection.

Keywords: Computer Vision
Abstract: Finding traversable paths using computer vision is one of the most important components of an intelligent mobile robot system. For a wall climbing robot that operates in an urban environment, it is essential to automatically detect surface types and orientations for switching between moving and climbing, and for applying different adhesive forces both to save energy and ensure its own safety. This paper presents a novel segmentation-based stereovision approach in order to rapidly obtain accurate 3D estimations of urban scenes with largely textureless areas and sharp depth changes. The new approach takes advantage of the fact that many man-made objects in an urban setting consist of planar surfaces. Our approach has three main components: extraction of natural (planar) matching primitives, stereo matching via three-step algorithm (global match, local match and plane fitting), and plane merging and parameter refinement. Experimental results are provided for real indoor scenes.

Keywords: Sensor Fusion, Sensor Networks, Agent-Based Systems
Abstract: In this paper, we provide a new two-layer scalable architecture, Intelligent Distributed Architecture (IDA). The first layer of IDA, the application layer, is responsible for the mission specific tasks. The second layer, the network layer, is responsible for relaying the information quickly to reduce latency. In order to increase efficiency, we propose an intelligent network layer that evaluates the network traffic through application provided policies. The evaluation assesses improved accuracy in bandwidth limited scenarios. IDA policies permit the application to drop, merge or modify the packets in real time from different sources. We demonstrate how this architecture can be applied to an example application, distributed target tracking. We also propose some new algorithms that can be used in conjunction with IDA for target tracking. Our experiments on this application show that IDA improves system performance when the bandwidth is limited.

Keywords: Sensor Networks, Localization, Surveillance Systems
Abstract: In camera sensor network research, physical camera sensor network platforms with low power and low cost are needed for testing and validating algorithms. It is also necessary that the camera nodes be calibrated precisely. In this work, we first develop and evaluate a low power and low cost wireless camera sensor network platform. The camera sensor nodes in this platform transmit a grayscale image over a wireless channel to a master control station. Then we propose a simple, light-weight algorithm to perform distributed calibration of the camera sensor nodes. The camera sensor nodes use their imaging abilities in collaboration with a cooperative moving target to determine their own positions and orientations. The proposed algorithm requires simple arithmetic calculations and hence it can be realized on low power processors. This calibration algorithm has been implemented and evaluated on the developed physical camera sensor network platform.

Keywords: Localization, Mapping, Recognition
Abstract: Mobile robots rely on their ability of scene recognition to build a topological map of the environment and perform location-related tasks. In this paper, we describe a novel lightweight scene recognition method using an adaptive descriptor which is based on color features and geometric information for omnidirectional vision. Our method enables the robot to add nodes to a topological map automatically and solve the localization problem of mobile robot in real-time. The descriptor of a scene is extracted in the YUV color space and its dimension is adaptive depending on the segmentation result of the panoramic image. Furthermore, the descriptor is invariant to rotation and slight changes of illumination. The robustness of the scene matching and recognition is tested through real experiments in a dynamic indoor environment. The experiment is carried out on a mobile robot equipped with an omnidirectional camera. In our tests, the average processing time is 30 ms for each frame including feature extraction, matching, and the adding of new nodes.

Keywords: Learning and Adaptive Systems, Sensor Networks
Abstract: This work focuses on the observation of environmental phenomena that occur as spatial distributions in two and three dimensions, using sensor-enabled mobile vehicles(ground,air or undersea). Algorithms to guide an adaptive exploration of a given region through systematic choice of sampling locations under the constraints imposed by vehicles are presented. Variation sensitive multiresolution sample distributions are achieved through an iterative variation sensitive estimation of the unknown process.

Keywords: Biomimetics, Legged Robots, Biologically-Inspired Robots
Abstract: Aiming to real easy application in several quadruped robot platforms, this paper introduces a new method of modeling central pattern generators (CPG) to control quadruped locomotion. Not only can this new model generate all the primary gaits of quadrupeds stably with limit cycle effect, but it also has the ability of tuning the periodic outputs with arbitrary waveforms. The core idea is to combine strong points of two mathematical tools: Fourier series and Recurrent neural networks. In addition, a new biomimetic controller is also introduced using the proposed CPG model and several reflex modules. Finally, dynamic simulations are performed to validate the efficiency of the proposed controller.

Keywords: Biologically-Inspired Robots, Biomimetics, Redundant Robots
Abstract: It is known that biologically inspired neural systems could exhibit natural dynamics efficiently and robustly for motion control, especially for rhythmic motion tasks. In addition, humans or animals exhibit natural adaptive motions without considering their kinematic configurations against unexpected disturbances or environment changes. In this paper, we focus on rhythmic arm motions that can be achieved by using a controller based on neural oscillators and virtual force. In comparison with conventional researches, this work treats neither trajectories planning nor inverse kinematics. Instead of those, a few desired points in task-space and a control method with Jacobian transpose and joint velocity damping are merely adopted. In addition, if the joints of robotic arms are coupled to neural oscillators, they may be capable of achieving biologically inspired motions corresponding to environmental changes. To verify the proposed control scheme, we perform some simulations to trace a desired motion and show the potential features related with self-adaptation that enables a three-link planar arm to make adaptive changes from the given motion to an compliant motion. Specifically, we investigate that human-like movements and motion repeatability are satisfied under kinematic redundancy of joints.

Keywords: Biologically-Inspired Robots, Biomimetics
Abstract: Many biologically inspired approaches have been investigated in relation with researches on mobile robot(s) that can effectively locate targets that induce gradient information. Here, we concentrate on realizing an adaptive searching behavior in mobile robot that is simple, yet effective with and without sensing the gradient information. We are interested in two searching behaviors found in biological creatures: bacterial chemotaxis, probably the simplest yet effective gradient sources searching behavior found in living creatures; and Levy walk, specialized random walks with fractal movement trajectories that optimize random search for sparsely and randomly distributed target(s). Our approach is to implement and combine the two searching behaviors based on “yuragi”, a Japanese word for biological fluctuation.

Keywords: Biologically-Inspired Robots, Behaviour-Based Systems, Legged Robots
Abstract: In this paper the compliant low level control of a biologically inspired control architecture suited for bipedal dynamic walking robots is presented. It consists of elastic mechanics, a low-level compliant joint controller and a hierarchical reflex-based control layer. The former is implemented on a DSP while the reflex network is located on a desktop PC. Thus, one is able to utilize distribution as a powerful means to guarantee low latency and scalability. The concept is tested on a prototype leg mounted on a vertical slider that is designed to perform cyclic squat jumps. Thus, a suited mechatronic setup that features highly dynamic actuators as well as energy storage capabilities is derived. Cyclical jumping is employed as a benchmark for the system's performance. Experimental results of the prototype setup as well as simulation runs are presented and compared to human squat jumping.

Keywords: Legged Robots, Adaptive Control
Abstract: In the present study, we investigate a control strategy for hopping motions of an articulated leg that is driven by series elastic actuation. A highly compliant spring in the knee joint allows the exploitation of periodic energy storage but creates a major control challenge by severely limiting the bandwidth of closed-loop position or force control. This handicap is intensified by slow actuators, substantial delays, and the kinematic coupling of the articulated design. With classic closed-loop control strategies failing, an adaptive open-loop control algorithm is presented, that, over a series of jumps, estimates the compression of the actuator springs, and gradually modifies the motor inputs in order to minimize slipping and create a purely vertical motion.

Keywords: Legged Robots, Motion Control, Biologically-Inspired Robots
Abstract: The main driving force behind research on legged robots has always been their potential for high performance locomotion on rough terrain and the outdoors. Nevertheless, most existing control algorithms for such robots either make rigid assumptions about their environments (e.g flat ground), or rely on kinematic planning with very low speeds. Moreover, the traditional separation of planning from control often has negative impact on the robustness of the system against model uncertainty and environment noise. In this paper, we introduce a new method for dynamic, fully reactive footstep planning for a simplified planar spring-mass hopper, a frequently used dynamic model for running behaviors. Our approach is based on a careful characterization of the model dynamics and an associated deadbeat controller, used within a sequential composition framework. This yields a purely reactive controller with a very large, nearly global domain of attraction that requires no explicit replanning during execution. Finally, we use a simplified hopper in simulation to illustrate the performance of the planner under different rough terrain scenarios and show that it is extremely robust to both model uncertainty and measurement noise.

Keywords: Legged Robots, Learning and Adaptive Systems
Abstract: We address the problem of foothold selection in robotic legged locomotion over very rough terrain. The difficulty of the problem we address here is comparable to that of human rock-climbing, where foot/hand-hold selection is one of the most critical aspects. Previous work in this domain typically involves defining a reward function over footholds as a weighted linear combination of terrain features. However, a significant amount of effort needs to be spent in designing these features in order to model more complex decision functions, and hand-tuning their weights is not a trivial task. We propose the use of terrain templates, which are discretized height maps of the terrain under a foothold on different length scales, as an alternative to manually designed features. We describe an algorithm that can simultaneously learn a small set of templates and a foothold ranking function using these templates, from expert-demonstrated footholds. Using the LittleDog quadruped robot, we experimentally show that the use of terrain templates can produce complex ranking functions with higher performance than standard terrain features, and improved generalization to unseen terrain.

Keywords: Legged Robots, Dynamics, Mechanism Design
Abstract: This paper investigates the efficiency of a 2-period gait from the kinetic energy view-point. First, we formulate a steady 2-period gait for a compass-like bipedal robot by using a simple recurrence formula for the kinetic energy of an asymmetric rimless wheel. Second, we theoretically show that, in the case that the mean value of the hip angle is constant, the generated 2-period steady gait is less efficient than a 1-period symmetric one in terms of kinetic energy. We also show that the symmetric gait is not always optimal from another viewpoint. We then investigate the validity of the derived method through numerical simulations of virtual passive dynamic walking. Other approaches, delayed feedback control and a quasi-constraint on the impact posture, are also considered for stabilization to a 1-period gait and their effects are discussed.

Keywords: Localization
Abstract: Sound source localization is an important feature in robot audition. This work proposes a sound source number and directions estimation method by using the delay information of microphone array. An eigenstructure-based generalized cross correlation method is proposed to estimate time delay between microphones. Upon obtaining the time delay information, the sound source direction and velocity can be estimated by least square method. In multiple sound source case, the time delay combination among microphones is arranged such that the estimated sound speed value falls within an acceptable range. By accumulating the estimation results of sound source direction and using adaptive K-means++ algorithm, the sound source number and directions can be estimated.

Keywords: Voice, Speech Synthesis and Recognition, Social Human-Robot Interaction
Abstract: In this article we present a new framework for auditory processing that combines feature extraction and grouping processes to form what we call audio proto objects. These proto objects combine an arbitrary number of audio features in a compact representation that allows a more precise sound localization and also better interfacing to behavior-control in robotics. We compare our standard sound localization system with the new approach in several scenarios to demonstrate the potential of the new approach.

Keywords: Virtual Reality and Interfaces, Telerobotics, Voice, Speech Synthesis and Recognition
Abstract: We built an acoustical telepresence robot named TeleHead, which has a user-like dummy head and whose movement is synchronized with the user's head movement in real time. An accurate-shape user-like dummy head improves sound localization accuracy, but making an accurate-shape user-like dummy head for all users is not realistic. There have been many efforts to simplify dummy heads without head movement in order to make a dummy head suitable for all users. Head movement also improves sound localization accuracy. Therefore, we are trying to simplify TeleHead’s head shape by taking the effect of head movement into consideration. In this work, we made two types of simplified dummy heads, a ball-like dummy head and a ball-like dummy head with a user-like pinna, and used them in sound localization experiments. The experimental results show that the pinna is very important for sound localization in the median plane. Head movement can improve sound localization and subjects can localize sound with another person’s pinna. However, it is hard for subjects to localize a sound without a pinna even with head movement. In addition, the acoustical characteristics of each dummy head are significantly different. The results indicate the possibility of using a ball-like dummy head with a generic pinna for acoustical telepresence robots.

Keywords: Humanoid Robots, Biologically-Inspired Robots, Autonomous Agents
Abstract: While a robot is moving, the joints inevitably generate noise due to its motors, i.e. ego-motion noise. This problem is very crucial, especially in humanoid robots, because it tends to have a lot of joints and the motors are located closer to the microphones than the sound sources. In this work, we investigate methods for the prediction and suppression of the ego-motion noise. In the first part, we analyze the performance of different noise subtraction strategies, assuming that the noise prediction problem has been solved. In the second part, we present some results for a noise prediction scheme based on the current robot joint status. Performance is evaluated for a number of criteria, including Automatic Speech Recognition (ASR). We demonstrate that our method improves recognition performance during ego-motion considerably.

Keywords: Marine Robotics, Mapping
Abstract: Detecting already-visited regions in vision-based navigation and mapping helps reduce drift and position uncertainties. Inspired from content-based image retrieval, an efficient approach is the use of emph{visual vocabularies} for measuring similarities between images. In this way, images corresponding to the same scene region can be associated. The state of the art proposals that address this topic suffer from two main drawbacks: (i) they require heavy user intervention, generally involving trial and error tasks for training and parameter tuning and (ii) they are suitable for batch processing only, where all the data is readily available before data processing. We propose a novel method for visual vocabulary navigation and mapping that overcomes these shortcomings. First, the vocabularies are built and updated on-line, during robot navigation, in order to efficiently represent the visual information present in the scene. Also, the vocabulary building process does not require any user intervention.

Keywords: Marine Robotics, Path Planning for Multiple Mobile Robot Systems, Sensor Networks
Abstract: By combining a low-order model of forecast errors, the extended Kalman filter, and classical continuous optimization, we develop an integrated methodology for planning mobile sensor paths to sample continuous fields. Agent trajectories are developed that specifically take into account the fact that data collected will be used for near real-time assimilation with large predictive models. This aspect of the problem has significant implications because the trajectories generated are very different from those which do not take the assimilation step into account, and their performance in controlling error is notably better.

Keywords: Marine Robotics, SLAM, Mapping
Abstract: In this paper we propose an approach to SLAM suitable for bathymetric mapping by an Autonomous Underwater Vehicle (AUV). AUVs typically do not have access to GPS while underway and the survey areas of interest are unlikely to contain features that can easily be identified and tracked using bathymetric sonar. We demonstrate how the uncertainty in the vehicle state can be modeled using a particle filter and an Extended Kalman Filter (EKF), where each particle maintains a 2D depth map to model the seafloor. Efficient methods for maintaining and resampling the joint maps and particles using Distributed Particle Mapping are then described. Our algorithm was tested using field data collected by an AUV equipped with multibeam sonar. The results achieved by Bathymetric distributed Particle SLAM (BPSLAM) demonstrate how observations of the seafloor structure improve the estimated trajectory and resulting map when compared to dead reckoning fused with USBL observations, the best navigation solution during the trials. Furthermore, the computational run time to deliver these results falls well below the total mission time, providing the potential for the algorithm to be implemented in real time.

Keywords: Animation and Simulation, Marine Robotics, Networked Robots
Abstract: Recent developments in cooperation of autonomous vehicles, potentially heterogeneous, have highlighted the interest of the roboticists community to this emerging research field. The issues raised by this kind of application are numerous (cooperative localisation, communication reliability, coordinated path planning, supervision...) and solutions are currently under development. A recurrent problem in this context is the logistics cumbersome and the high risk of damaging a robot in case of a default (scenario, communication, algorithm, failure of another robot...). Therefore all teams involved in this type of research have developed or intend to develop a simulator to run realistic and efficient preliminary tests.

Many simulators exist and are currently used to test and validate strategies and control laws. Yet few are usable in the context of the collaborative mission planning. Thus, the aim of this paper is to review the available tools defining in a first step the necessary requirements to cope with this context. In order to get a complete overview of these tools, we propose a new classification that we use to sort the existing simulators. It is to be noted that we focus our interest on simulators which can at least address the problem of marine robotics.

None of the available simulators being compliant with the previous requirements, we propose a new simulation architecture. Thetis is a real-time multi-vehicles hybrid simulator for heterogeneous vehicles. This simulator allows Hardware In The Loop (HIL) simulations including the use of virtual sensors which allows to provide a representation of a virtual world, and includes the support of communication devices. The included acoustic propagation model allows communications between the vehicles. The architecture of this simulator is conceived so that it ensures a temporal decoupling between the virtual environment, the vehicles, sensors and communication simulators and, of course, the actual embedded controller which warrants the quality of the results.

Keywords: Force and Tactile Sensing, Physical Human-Robot Interaction, Contact Modelling
Abstract: We propose a solution which combines haptic sensing with safe interaction, at low cost. Contact locations are made through a flexible sheet of tactile binary switch matrix. This sheet covers the surface of a rigid bumper module assembled to the robot's basic link through a distributed force sensing units. Combination of location and force provides the haptic sensing module. The haptic system is covered with a flexible outer material which role is to absorb contact impacts and to cast local surface profile on which the robot can take support. This overall system allows having a combined haptic sensing with safe and robust physical interaction with both the environment and the human using active compliance. We discuss the benefit of such a simple and modular concept and present how to design the cover material. A simple prototype is realized and experienced.

Keywords: Animation and Simulation, Haptics and Haptic Interfaces, Micro-manipulation
Abstract: In this paper, a new tool dedicated to the analysis and the conception of molecules is presented. It is composed of an adaptive simulation software and a haptic device used to interact with molecules while feeling either the forces applied by the environment or the internal forces. The adaptive articulated body algorithm allows fast simulations of complex flexible molecules. To handle the coupling with the force feedback device, two different control schemes designed for nanoscale applications and providing high transparency rendering are proposed and compared.

The system we propose is highly flexible since either a single rigid body or the entire molecule can be manipulated via the haptic device. The user can choose between setting a desired position/orientation of the molecule, or apply forces/torques to manipulate it. It allows the operator to control each stage of the design process of new molecular structures.

The validity of this tool is demonstrated through examples of haptic interaction between the HIV protease and its inhibitors, and unfolding one of these drugs.

Keywords: Force and Tactile Sensing, Grasping, Domestic Robots
Abstract: In this paper, we present a novel approach for identifying objects using touch sensors installed in the finger tips of a manipulation robot. Our approach operates on low-resolution intensity images that are obtained when the robot grasps an object. We apply a bag-of-words approach for object identification. By means of unsupervised clustering on training data, our approach learns a vocabulary from tactile observations which is used to generate a histogram codebook. The histogram codebook models distributions over the vocabulary and is the core identification mechanism. As the objects are larger than the sensor, the robot typically needs multiple grasp actions at different positions to uniquely identify an object. To reduce the number of required grasp actions, we apply a decision-theoretic framework that minimizes the entropy of the probabilistic belief about the type of the object. In our experiments carried out with various industrial and household objects, we demonstrate that our approach is able to discriminate between a large set of objects. We furthermore show that using our approach, a robot is able to distinguish visually similar objects that have different elasticity properties by using only the information from the touch sensor.

Keywords: Force and Tactile Sensing
Abstract: We present a setup for simple and fast experimental estimation of drag coefficients. Our system can accurately determine the parameters of fluid-object interaction for complicated geometry and boundary conditions in the realm of classical Navier-Stokes equations. Obtained results are compared with theoretical and numerical solutions. Good agreement with those references is achieved in both cases. An advantage of our method is the prompt and easy parameter retrieval that still maintains appropriate accuracy. Comparable detailed numerical estimations run on the order of hours or days.

Keywords: Marine Robotics, Localization, Range Sensing
Abstract: This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. An Extended Kalman Filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600m path within an abandoned marina underwater environment with satisfactory results.

Keywords: Marine Robotics, Localization, Field Robots
Abstract: In this paper we present a general framework for predicting the positioning uncertainty of underwater vehicles. We apply this framework to common examples from marine robotics: standalone long baseline (LBL) positioning and integrated LBL reference and Doppler velocity log (DVL) dead-reckoning.

The approach is based on formulating positioning as an estimation problem. Using simple sensor models for the most common information sources, we show how the the Cramer-Rao lower bound can be used to predict the system-level navigation performance. The resulting three dimensional covariance matrix is then summarized using scalar performance metrics based on the notion of dilution of precision (DOP), a well-known metric from the global positioning system (GPS) community. To illustrate this general tool, we present the answers to a few particular questions: How does the baseline length affect the solution for standalone LBL positioning? When using DVL and heading odometry, how precise is the combined DVL/LBL solution? For an integrated DVL/LBL solution, what is the required update rate from the absolute reference to constrain odometry drift? What is the relative importance of heading, odometry and range precision for overall performance?

We substantiate our estimation framework through experimental evidence which shows that the analytical predictions are consistent with performance in the field.

Keywords: Marine Robotics
Abstract: For the purpose of detecting CO2 leaks during ocean CO2 sequestration, underwater robots that can make observations independently and stay over the seabed against the current for long periods of time are needed. In order to achieve this objective, a novel tether mooring type underwater robot was proposed. The robot is moored, its position is controlled by changing the length of the tether. In addition, it can sustain itself with a sea current power generation system. After that, the prototype underwater robot “Anchor Diver” was developed. Anchor Diver is moored by one tether, moves using horizontal and vertical rudders and goes upstream by reel mechanism. In addition, the use of a movable anchor and generator as a propeller enables Anchor Diver to enlarge its range of activity. This paper describes the detailed development of Anchor Diver and underwater experiments.

Keywords: Manipulation Planning, Path Planning for Manipulators, Navigation
Abstract: Path planning in unknown environments such as Mars or underwater are not only challenging but also daunting tasks. While significant advances are made for mobile platforms, manipulator motion planning in unknown environments still falls short of full fledged solutions due to the uncertainty and complexity of higher order configuration spaces. Most feasible solutions proposed so far are either modeling unknown environments in realtime or applying randomized model based planners with sensitive skin type sensors. Although solving unknown environment planning problems with randomized model based approaches seems very promising, no systematic study has been reported as to how to adopt model based planners into the sensor based problem domain effectively. In this paper, we study the adoption issues of model based planners to tackle sensor based planning problems, and hence provide conversion guidelines from one to other problem domain. In addition, we discuss the range effect of the sensitive skin type sensor, IPA, for on-line planning in unknown environments. Some experimental results in an unknown environment are presented in the paper as well.

Keywords: Path Planning for Manipulators, Motion Control, Dynamics
Abstract: This paper reports a motion planning scheme for a high performance robot aiming to realize the motion control skills exhibited by professional golfers. The robot has a dexterous mechanism with similar distribution of actuators' capability and a pair of mechanical joint stops like human beings. The proposed motion planning method combines target dynamics together with port-controlled Hamiltonian (PCH) system theory resulting in an energy controller which not only takes the mechanical joint stops into account but also realizes torque compensation from a high-power actuator to a low-power actuator. Simulation and experimental results prove the proposed method can generate the golf swings with specified hitting speed and finish position for our specially designed robot.

Keywords: Manipulation Planning, Grasping
Abstract: Sensorless localization of 3D objects has been a significant research topic for many years. Researchers have focused on this problem from both theoretical and practical perspective where the goal is to reduce uncertainties in the orientation of a 3D object. However, to the best of our knowledge, no effective practical methods have been proposed so far to localize a polyhedron from any initial orientation to a unique orientation without sensors.

In our previous work, two broad classes of 3D objects have been introduced, which can be localized from an arbitrary state to a unique state on a flat plane (the surface resting on the flat plane is established) without sensors. In this paper, a much broader class of polyhedra is introduced, which can be localized to a unique state without sensors. The main contributions of this paper are given as follows: ² It is found that a polyhedron with an arbitrary initial state on the flat plane can be rotated to a fixed orientation (the orientation of the surface resting on the flat plane is fixed), provided that the polygon corresponding to each surface of the polyhedron can be oriented to a unique orientation in a 2D space. The method of rotating the polyhedron to a fixed orientation is given. ² Base on the above result, both conditions and the strategy are given for a polyhedron to be localized to a unique state. ² An example is given to show the validity of the strategy.

Keywords: Manipulation Planning, Redundant Robots, Parallel Robots
Abstract: In this paper, two torque assignment methods of the antagonistic stiffness for a 2-DOF planar parallel manipulator are presented and verified by experiments. The first method is equalizing the magnitude of the stiffness in all directions at a desired position. The second method is maximizing the active stiffness in one direction at a given path. A 2-DOF parallel mechanism with four actuators is used for verification tests, where the internal torque of the mechanism exists on the two dimensional null space. In the experiment, passive and active stiffness are tested when endowing the external force at the moving platform and compared with the estimated results.

Keywords: Manipulation Planning, Redundant Robots, Nonholonomic Motion Planning
Abstract: We consider the problem of planning collision-free motions for general (i.e., possibly nonholonomic) redundant robots subject to task space constraints. Previous approaches to the solution are based on the idea of sampling and inverting the task constraint to build a roadmap of task-constrained configurations which are then connected by simple local paths; hence, task tracking is not enforced during the motion between samples. Here, we present a control-based randomized approach relying on a motion generation scheme that guarantees continued satisfaction of such constraint. The resulting planner allows to achieve accurate execution of the desired task without increasing the size of the roadmap. Numerical results on a fixed-base manipulator and a free-fying mobile manipulator are presented to illustrate the performance improvement obtained with the proposed technique.

Keywords: Calibration and Identification, Range Sensing, Computer Vision
Abstract: Outdoor camera networks are becoming ubiquitous in critical urban areas of large cities around the world. Although current applications of camera networks are mostly limited to video surveillance, recent research projects are exploiting advances on outdoor robotics technology to develop systems that put together networks of cameras and mobile robots in people assisting tasks. Such systems require the creation of robot navigation systems in urban areas with a precise calibration of the distributed camera network. Despite camera calibration has been an extensively studied topic, the calibration (intrinsic and extrinsic) of large outdoor camera networks with no overlapping view fields, and likely to suffer frequent recalibration, poses novel challenges in the development of practical methods for user-assisted calibration that minimize intervention times and maximize precision. In this paper we propose the utilization of Laser Range Finder (LRF) data covering the area of the camera network to support the calibration process and develop a semi-automated methodology allowing quick and precise calibration of large camera networks. The proposed methods have been tested in a real urban environment and have been applied to create direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms.

Keywords: Calibration and Identification, Computer Vision
Abstract: This paper considers the issue of calibrating a camera with narrow angular field of view using standard, perspective methods in computer vision. In doing so, the significance of perspective distortion both for camera calibration and for pose estimation is revealed. Since narrow angular field of view cameras make it difficult to obtain rich images in terms of perspectivity, the accuracy of the calibration results is expectedly low. From this, we propose an alternative method that compensates for this loss by utilizing the pose readings of a robotic manipulator. It facilitates accurate pose estimation by nonlinear optimization, minimizing reprojection errors and errors in the manipulator transformations at the same time. Accurate pose estimation in turn enables accurate parametrization of a perspective camera.

Keywords: Computer Vision
Abstract: A simple flexible technique is proposed to easily calibrate five intrinsic parameters a camera based on the three side lengths of a triangle. The technique only requires taking the template with a triangle, and matching the three vertices of the triangle between the template and its image. Analytical solution is given to guarantee algorithm accomplishment successfully. The essential relations for intrinsic parameters of camera were discussed in theory and the calibration algorithm efficiency was rigorously and completely analyzed. At present depth estimation of an object in computer vision and robotics is most commonly done by triangulating and estimating distance from two cameras. Depth estimation from a camera is deeply investigated in this paper. The real data experimental results show that the techniques are very simple high accurate and efficient.

Keywords: Computer Vision, Calibration and Identification, Range Sensing
Abstract: Solving visual features' correspondence and dealing with missing data are two factors of limitations for points registration techniques. To tackle this problem, we conceived a pattern, primarily designed for structured lighting vision systems, which may also be used for camera calibration purposes. The pattern design previously presented in cite{Albitar07-iccv} provides a huge of benefits. Among them, we firstly present a new calibration technique of a structured lighting system and secondly an automatic distortion compensation based on a printed pattern. These two well-known issues are very useful in 3D vision-based metrology with range data, for instance for model-based visual robot control, especially when the model is incrementally built with a real-time 3-D reconstruction of moving surfaces. Perhaps, one of the most significant profit with a high Hamming distance pattern is the ability to reliably decode its projected individual elements even if several of items are missing, as it greatly extends the range of measurements volume. A technique which solves the distortion parameters by means of a robust M-estimator algorithm is presented. It uses a printed pattern and it allows the distortion be corrected with a single view and without the computation of other (intrinsic/extrinsic) parameters, even in presence of occlusions. Experimental results, in one hand by means of a printed pattern for the distortion compensation of a rigid endoscope and on the other hand by means of a projected pattern for the calibration of the structured lighting system, show very good performance for the 3-D reconstruction.

Keywords: AI Reasoning Methods, Intelligent Vehicles
Abstract: In this paper, we deal with an original Advanced driver assistance system (ADAS) based on the use of omnidirectional vision and an evidential fusion architecture. The panoramic perception solution permits us to address efficiently the problem of close vehicles detection but also the monitoring side traffic system. The fusion and integration of this sensorial data stream is assumed by a credibilist architecture based on the Transferable Belief Model (TBM) of Smets. This paradigm permits the filtering of false alarms efficiently by an optimal management of the uncertainties estimation.

Keywords: Recognition, Computer Vision, Intelligent Vehicles
Abstract: In this paper we introduce a real-time traffic light recognition system for intelligent vehicles. The method proposed is fully based on image processing. Detection step is achieved in grayscale with spot light detection, and recognition is done using our generic “adaptive templates”. The whole process was kept modular which make our TLR capable of recognizing different traffic lights from various countries. To compare our image processing algorithm with standard object recognition methods we also developed several traffic light recognition systems based on learning processes such as cascade classifiers with AdaBoost. Our system was validated in real conditions in our prototype vehicle and also using registered video sequence from various countries (France, China, and U.S.A.). We noticed high rate of correctly recognized traffic lights and few false alarms. Processing is performed in real-time on 640x480 images using a 2.9GHz single core desktop computer.

Keywords: Computer Vision, Intelligent Vehicles, Field Robots
Abstract: Road network information (RNI) simplifies autonomous driving by providing strong priors about driving environments. Its usefulness has been demonstrated in the DARPA Urban Challenge. However, the need to manually generate RNI prevents us from fully exploiting its benefits. We envision an aerial image analysis system that automatically generates RNI for a route between two urban locations. As a step toward this goal, we present an algorithm that extracts the structure of a parking lot visible in an aerial image. We formulate this task as a problem of parking spot detection because extracting parking lot structures is closely related to detecting all of the parking spots. To minimize human intervention in use of aerial imagery, we devise a self-supervised learning algorithm that automatically obtains a set of canonical parking spot templates to learn the appearance of a parking lot and estimates the structure of the parking lot from the learned model. The data set extracted from a single image alone is too small to sufficiently learn an accurate parking spot model. To remedy this insufficient positive data problem, we utilize self-supervised parking spots obtained from other aerial images as prior information and a regularization technique to avoid an overfitting solution.

Keywords: Computer Vision, Intelligent Vehicles, Intelligent Transportation Systems
Abstract: Generating a depth map from a pair of stereo images is a challenging task, which is often further complicated by the additional restrictions imposed by the target application; in the automotive field, for example, real-time environment reconstruction is essential for safety and autonomous navigation systems, thus requiring reduced processing times, often at the expense of a somewhat limited degree of accuracy in the results. Nevertheless, a-priori knowledge on the intended use of the algorithm can also be exploited to improve its performance, both in terms of precision and computational burden. This paper presents three different approaches to incremental Disparity Space Image (DSI) computation, which leverage the properties of a stereo-vision system installed on a vehicle to produce accurate depth maps at sustained frame rates on commodity hardware.

Keywords: Dexterous Manipulation, Redundant Robots, Parallel Robots
Abstract: When hyper redundant robots are used in complex and unpredictable environments such as human living space, they should deal with various contact conditions between surrounding objects. Robots thus should plan and optimize not only applying force to the object but also its distribution among contact area. This paper defines the ability to optimize stiffness distribution of a number of contact points as "Flexibility" and proposes elastic closed-loop mechanism which has a serial chain of revolute joints with torsion coil springs as a lightweight and supple hyper redundant mechanism. Output stiffness is formulated based on the minimization of potential energy, the balancing of internal force and the velocity constraint to construct a closed-loop mechanism. Joint input to obtain both the desired stiffness distribution and desired output position simultaneously is derived from partial derivative of the output stiffness and compensation by a learning control scheme. Motion control experiments with a 10R elastic closed-loop robot demonstrate the effectiveness of the proposed control scheme.

Keywords: Evolutionary Robotics
Abstract: An autonomous mobile robot requires an onboard controller that allows it to perform its tasks for long periods in isolation. One possibility is for the robot to adapt to its environment using some form of artificial intelligence. Evolutionary techniques such as genetic programming (GP) offer the possibility of automatically programming the controller based on the robot's experience of the world. Grammatical evolution (GE) is a recent evolutionary algorithm that has been successfully applied to various problems, particularly those for which GP has been successful. We present a method for applying GE to autonomous robot control and evaluate it in simulation for the Khepera robot.

Keywords: Dexterous Manipulation, Manipulation and Compliant Assembly, Biologically-Inspired Robots
Abstract: This paper deals with mechanical stiffness control of multi-DOF joint. It fundamentally mimics the skeleto-muscular system of human articulation, in which at least two muscles handle one rotary axis under their antagonistic (counteractive) action. In the first part of the paper one introduces basic formula for controlling the multi-DOF rotary joint that is assumed to be driven by a couple of novel actuators called ANLES (Actuator with Non-Linear Elastic System). It mimics a skeletal muscle in the sense of having a non-linear elasticity. Next the paper describes the structure of the ANLES that is designed and constructed for controlling the wrist joint of an anthropomorphic robot. The experimental results using one DOF joint controlled by a pair of ANLES reveal that the joint angle and the joint stiffness can be independently controlled by the proposed formula.

Keywords: Agent-Based Systems, Biomimetics, Autonomous Agents
Abstract: This paper investigates a perimeter patrol control problem in which multiple agents travel back and forth defending a border. A decentralized control inspired from the adaptive immune system TH1/TH2 differentiation mechanism has been proposed. The resulting patrol control exhibits robustness under adversarial conditions. This is primarily because the motion period can be arbitrary, which makes it difficult for intruders to find weak spots for attack. Moreover, this immuno-inspired control can avoid collision and automatically recover from agent failure.

Keywords: Sensor Networks, Localization
Abstract: Biologically-inspired swarm of robots with collaboration towards a common mission has a broad range of applications. However, the required dynamic localization among autonomous robots for such swarm collaboration, though usually implicitly assumed, has not been properly studied. In this paper, we address the roles of multiple antennas in localization and energy-efficient wireless communications for a swarm of robots. Following the gradient of signal powers along a trajectory, a robot can track the direction of a source robot. With three or more properly placed antennas that sense different phase shifts of carrier, a robot can localize a source. By lateration, three collaborative robots can localize a source with known distances to it. Via angulation technique, three robots can determine their geometric relationship with knowing two angles and one distance between them. The techniques can be extended from the 2-D to the 3-D space for application of wall-climbing robots. On the basis of knowledge of robot locations, beamforming techniques can be employed to receive and transmit signal towards the desired robot therefore improving energy efficiency and prolonging robot lifetime.

Keywords: SLAM, Service Robots, Learning and Adaptive Systems
Abstract: Acting in everyday-life environments is still a great challenge in service robotics. Although algorithms and solutions already exist for many relevant subproblems, in particular the aspect of robustness and suitability for everyday use has been neglected so far very often. Robustness and suitability for everyday use are features affecting not only the overall system design but have impact on each single algorithm of each component.

Although an overwhelming amount of work is available to address the SLAM problem, the challenge of applying a SLAM algorithm over the whole lifecycle of a service robot, perhaps even in different environments, has not been brought into focus very often. An obvious problem to be solved is the continuously growing number of landmarks. A lifelong running SLAM approach requires means to select landmarks such that they best cover the working environment given bounded SLAM resources like the maximum number of manageable landmarks.

This paper proposes a novel solution for selecting appropriate landmarks to limit the number of landmarks. The idea is to quantify the contribution of a landmark to the ability of the robot to localize itself in its working environment. Thus, the core contribution is to base the landmark selection process upon the landmarks' coverage of the working environment.

Real-world experiments on a P3DX-platform with a bearing-only SLAM approach and an omnicam confirm that the addressed question and the proposed first approach might be another step towards the overall goal of suitability for everyday use.

Keywords: Motion Control, SLAM, Sensor Fusion
Abstract: SLAM is a well studied technique for robots to build a map of environments while at the same time keeping track of their pose (position and orientation). However SLAM does not provide control approaches for how the robot moves around the environment. This paper presents an integrated approach to create a fully autonomous exploring and mapping robot. An EKF-SLAM approach is used to fuse Advanced Sonar and Laser Scan-Matching. This also tackles the problem of map-drifts in some types of environment where lasers do not supply sufficient information in some directions such as along a corridor. In addition, the proposed exploration algorithm takes advantage of the characteristic of the Voronoi Graph to enable the robot to strategically explore the environments in a loop-closing fashion and safe manner. By revisiting areas to close loops as early as possible, the robot can build a more stable map incrementally while still reliably tracking its pose. Experimental results of the integrated approach are shown to demonstrate the algorithm provides real-time exploration of a mobile robot in an initially unknown real environment. Experimental comparisons of exploration strategies with and without early local loop closing demonstrate the benefits of the approach in the map quality.

Keywords: SLAM, Localization, Service Robots
Abstract: In this paper we present a novel approach to estimate the trajectory of a robot by means of inexpensive passive RFID tags and odometry in unknown environments. We show how trajectory estimation, a prerequisite of mapping RFID transponder positions without a reference positioning system, can be achieved using a particle filter. The presented technique is based on a non-parametric model of spatial relationships between RFID measurements. It overcomes the noisy nature of RFID measurements and the absence of distance and bearing information. The accuracy of our method is investigated in a series of experiments with a mobile robot.

Keywords: Kinematics, Field Robots, Legged Robots
Abstract: Intelligent Mobility Platform with Active Spoke System (IMPASS) is a novel wheel-leg hybrid robot that can walk in unstructured environments by stretching in or out three independently actuated spokes of each wheel. This form of novel locomotion has the potential to combine the efficiency of a wheeled robot and the mobility of a legged robot. A highly mobile robot such as IMPASS could prove very valuable in applications where the terrain is complex and dangerous, such as search and rescue, reconnaissance, or anti-terror response. This video presents the experiments and findings of a variety of gaits for straight-line walking, transitions, and turning. Assuming no slip at the feet, with the 1-1 and 2-2 straight walking gaits, the robot can move forward stably but with different kinematic constraints. Unlike other wheeled vehicles which use Arckerman steering or differential steering, IMPASS can implement novel turning gaits even though the left and right hubs rotate with the same angular velocity. Steady state turning gait is demonstrated with skew transitions. Additionally, a free form gait is demonstrated using joystick control with interesting observations.

Keywords: Aerial Robotics, Sensor Networks, Distributed Robot Systems
Abstract: The Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control, a fleet of quadrotor helicopters, has been developed as a testbed for novel algorithms that enable autonomous operation of aerial vehicles. The testbed has been used to validate multiple algorithms such as reactive collision avoidance, collision avoidance through Nash Bargaining, path planning, cooperative search and aggressive maneuvering. This article briefly describes the algorithms presented and provides references for a more in-depth formulation, and the accompanying movie shows the demonstration of the algorithms on the testbed.

Keywords: Domestic Robots, Physical Human-Robot Interaction, Biologically-Inspired Robots
Abstract: “AWE” is a programmable “Animated Work Environment” supporting everyday human activities, at home, work and school, in an increasingly digital society. AWE features a novel robotic “wall,” three horizontal, reconfigurable work surfaces, and embedded information technologies. The video shows AWE as a digital simulation moving through six standard wall-desk configurations, interspersed with still photos and video clips of people interacting with the physical, full-scale, working prototype. The video also shows AWE beginning to behave intelligently as well as users fine-tuning AWE’s configurations by gesturing proximity sensors mounted at the hinges between wall panels. Usability testing suggests that AWE clearly adapts to variations in complex activities involving users working or playing in a single physical space with both physical and digital tools and artifacts.

Keywords: Mechanism Design, Smart Actuators, Flexible Arms
Abstract: A soft, controllably morphable mobile robot is an ideal platform for traversing complex terrain and navigating small holes. iRobot Corporation and the University of Chicago have made use of a phenomenon known as particle jamming to create such a robot. The robot presented in this work uses jamming skin cells to enable controlled morphing and locomotion.

Keywords: Legged Robots, Humanoid Robots
Abstract: This video highlights work to date on the Yobotics-IHMC Lower Body Humanoid Robot. The robot is a twelve degree-of-freedom robot with force controllable Series Elastic Actuators at each degree of freedom. Control algorithms utilize Virtual Model Control, and foot placement is determined using Capture Regions. The robot can recover from moderate disturbances and walk on flat ground. Ongoing work is focused on improving robustness to disturbances, walking more quickly and efficiently, and walking over rough terrain.

Keywords: Biologically-Inspired Robots, Legged Robots, Autonomous Agents
Abstract: For decades, insects have been a valuable source of inspiration for mechanical and control designs of legged robots. Anatomical and behavioral studies of insects such as cockroaches, stick insects and locusts have inspired the development of many robots. However, their control systems had to be engineered based upon behavioral studies and control hypotheses rather than neurobiology. Recent insect neurobiological discoveries now make it possible to control the legs of robots with a network found to control the legs of stick insects. In previous work this network we have dubbed SCASM (Sensory-Coupled Action Switching Modules) was shown coordinating the joints of a robot leg and adapting its normal leg cycle to irregularities in the terrain. We also showed that the SCASM network can be implemented effectively on a simple micro-controller with little computational power. This video describes additional sensory connections that, when added to SCASM, generate elevator and searching reflexes. We also show for the first time an autonomous hexapod robot walking over irregular terrain using a SCASM network to control each of its six legs and a Cruse type network to control its gait using only on-board, simple micro-controllers.

Keywords: Cellular and Modular Robots, Biologically-Inspired Robots, Distributed Robot Systems
Abstract: In nature, animal groups achieve robustness and scalability with each individual executes a simple and adaptive strategy. Inspired by this phenomenon, we propose a decentralized control framework for modular robots to achieve coordinated and self-adaptive tasks with each modules performs simple distributed sensing and actuation [1]. In this demonstration, we show that such a framework allows several different modular robotic systems to achieve self-adaptation tasks scalably and robustly, examples tasks include module-formed table and bridge that adapt to constantly-perturbed environment, a 3D relief display that renders sophisticated objects, and a tetrahedral robot that performs adaptive locomotion.

Keywords: Humanoid Robots, Path Planning for Manipulators
Abstract: This video illustrates our work on contact points planning and its recent enhancement by two new functionalities. First, by taking advantage of the possibilities offered by our initial posture generator, we include additional tasks in the planning that are not related to locomotion. Second, we refine the potential function that guides the planner so as to cope with more challenging scenarios. We then test these novelties on difficult problems with success, and experiment the output of one of the planned scenario on a HRP-2 humanoid robot.

Keywords: Micro/Nano Robots, Biologically-Inspired Robots, Legged Robots
Abstract: DASH, or the Dynamic Autonomous Sprawled Hexa- pod, is a small, high-power density, minimally actuated robot capable of high-speed running and surviving large falls. The design of DASH has been informed by the study of nature’s greatest runners from whom scientists have derived many models for robust high-speed locomotion. DASH is constructed using a scaled Smart Composite Manufacturing (SCM) process which creates rigid cardboard beams with flexible polymer joints that can be folded into complex functional elements. DASH utilizes an alternating tripod gait, and the mechanism by which it creates an alternating tripod gait from a single DC motor is presented. DASH is 10 cm long, has a mass of 16.2 grams, and is capable of running straight at speeds of 1.5 m/s, or 15 body-lengths per second, which is as fast as other similar legged runners in body-lengths per second. Both real time and slow-motion video of high-speed running are shown. A lightweight servomotor can modify the kinematics of DASH so that turning moments are generated. The cardboard beams from which DASH is constructed are rigid in directions which allow for sufficient power transmission for high-speed running. The beams are also flexible but resilient to off-aixs forces and moments which allow DASH to contort and absorb energy under forces not normally seen during running. This property helps to enable DASH survive large falls without damage, including drops from 28 meters onto concrete.

Keywords: Mechanism Design, Search and Rescue Robots
Abstract:

Keywords: Animation and Simulation, Virtual Reality and Interfaces, Haptics and Haptic Interfaces
Abstract: In this video we present a physics-based haptic simulation designed to teach basic suturing techniques for simple skin or soft tissue wound closure. The pre-wound suturing target, skin or deformable tissue, is modeled as a modified mass-spring system. The suturing material is designed as a mechanics-based deformable linear object. Tools involved in the live suturing procedures are also simulated. Collisions between the soft tissue and the needle, the soft tissue and the suture are analyzed. In addition to modeling the detail steps involved in a typical suturing procedure, modeling approaches for evaluation of a stitch are also discussed.

Keywords: Entertainment Robotics, Wheeled Robots
Abstract: This video shows a continuing work of the glove puppet robot presented before [1]. The major improvement from the previous work is to mount the 9-DOF mechanism, which mimicking a glove puppet manipulation, on a two-wheel mobile platform. The platform provides agile movements of the robot but itself is an unstable system. Hence, a self-balancing controller is implemented by considering the motion as well as configuration variation of the upper body (the 9-DOF mechanism). The control law utilizes the principle of computed torque method with online identification of related parameters using various sensors including an accelerometer. The incline angle is obtained by fusing a gyroscope and a tilt sensor. Under the balancing control, the forward motion of the robot is achieved by giving a desired tilt angle profile. To minimize the footprint of electronics, the controller is implemented using an 8-bit single-chip microcontroller. Further, to enhance the interaction capability of the system, a simple gesture coding using dynamic time warping[2] identification method with Markov model is implemented for the data glove to recognize the puppet gesture by human hand.

Keywords: Micro-manipulation, Micro/Nano Robots, Biologically-Inspired Robots
Abstract: The video shows an aggregate of approximately 5000 MC-1 flagellated bacteria being controlled by computer to transport and assemble blocks in order to build a Step pyramid. In this example, the pyramidal structure was built one block at a time and took approximately 15 minutes to complete.

Keywords: Humanoid Robots, Dynamics, Manipulation Planning
Abstract: There are many kinds of large, heavy objects, or objects with geometrical constraints in our daily life, but non-fixed robots such as humanoid robots are still not able to manipulate them sufficiently well. In this paper we focus on a swing door as a heavy object with geometrical constraints, and present a method for the humanoid robots to open it by using impulsive forces. We first discuss on momentum transfer from the robot to the door. Then we propose a method of generating a whole body motion to impact on the door. We analyze the dynamic model of the door, and we confirm the validity of our method through simulation. At last, we realize a motion of the robot opening a swing door quickly by the method in experiment with the HRP-2 robot hardware.

Keywords: Humanoid Robots, Path Planning for Manipulators
Abstract: This paper extends our previous work on contact points planning in two ways. First, by taking advantage of the possibilities offered by our initial posture generator, we include additional tasks that are not related to locomotion within the planning. The output motion will be generated so as to cope with these tasks. Second, we refine the potential function that guides the planner by introducing potential fields acting each on a single body. This helps escaping local minima of the original potential field and thus to deal with more challenging scenarios. We then test these novelties on difficult problems with success, and experiment the output of one of the planned scenario on a HRP-2 humanoid robot.

Keywords: Humanoid Robots
Abstract: Optimal motions are usually used as joint reference trajectories for repetitive or complex motions. In the case of soccer robots, the kicking motion is usually a benchmark motion that is computed off-line, and thus without taking into account the current position of the robot or the direction of the goal. Moreover, robots must react quickly to any situation, even if not expected, and cannot spend time to generate a new optimal motion by the classical way. Therefore, we introduce a new method for fast motion re-planning based on an off-line computation of the feasible set of motion parameters, using Interval Analysis.

Keywords: Humanoid Robots, Contact Modelling
Abstract: In order to exert a large force on the environment, it is effective to apply impulsive force. We describe the motions that perform tasks by applying impulsive force as ``impact motion.'' This paper presents a contact dynamics model of a humanoid robot for such a motion. Multibody dynamics and effect of a servo controller on impulsive force are also considered in the proposed model. The proposed model can estimate impulsive force at low computation cost compared with full-featured dynamics computation methods. The estimation results of each motion are compared with simulation results by OpenHRP3. The maximum error of impulse is about 6 (%). Therefore, the proposed model is useful for estimating dynamics behavior of a humanoid robot.

Keywords: Humanoid Robots, Contact Modelling, Dynamics
Abstract: This paper presents a methodology for the modeling and control of internal forces and moments produced during multi-contact interactions between humanoid robots and the environment. The approach is based on the virtual linkage model which provides a physical representation of the internal forces and moments acting between the various contacts. The forces acting at the contacts are decomposed into internal and resulting forces and the latter are represented at the robot's center of mass. A grasp/contact matrix describing the complex interactions between contact forces and center of mass behavior is developed. Based on this model, a new torque-based approach for the control of internal forces is suggested and illustrated on the Asimo humanoid robot. The new controller is integrated into the framework for whole-body prioritized multitasking enabling the unified control of operational tasks, postures, and internal forces.

Keywords: Physical Human-Robot Interaction, Haptics and Haptic Interfaces, Visual Tracking
Abstract: Although it is reported in the literature that haptic feedback leads to improved performance in kinesthetic collaborative tasks, it has not been investigated so far whether this advantage is accompanied by a higher physical workload. This paper is an initial effort to examine efficiency in haptic interaction: We relate physical effort to a performance outcome in a virtual pursuit tracking task. An experimental study is conducted to compare efficiency in a collaborative mutual haptic feedback condition to three control conditions, where participants either acted alone or collaboratively without haptic feedback from the partner. Results show that reciprocal haptic feedback does not improve efficiency, although participants' performance was generally improved when doing the task with a partner, relative to executing it alone. This is due to the greater effort associated with physical connection between partners. However, the effort is more fairly distributed between partners when haptic feedback from the partner is provided. Haptic feedback may be more efficient when the amount of necessary communication between partners increases compared to the task studied here.

Keywords: Physical Human-Robot Interaction, Motion Control, Force Control
Abstract: The development of a robot motion control scheme and a mechanical load adjuster with a motion measurement interface is addressed in this paper. To improve the efficiency of a task involving human-robot cooperation, we designed a novel robot control system, in which a multiple-load state can be provided for a human operator. This system also can provide a multiple-dynamics state during a task involving human-robot dynamical cooperation. The multiple-load state including its transition is effective and efficient in such a task. A single load state can be easily provided by the impedance control of the robot motion thus far; however, the multiple-load state and its transition are difficult to realize using a conventional control scheme. The proposed control scheme differs widely from a conventional impedance control scheme in that the multiple-load state as well as both active and passive states cannot be induced in the single robotic system. Under the proposed control scheme, the load state can be adjusted with the various dynamics in the active or passive state. To confirm the effectiveness of the proposed control system, human-robot cooperative experiments were carried out. Results showed that the proposed control scheme can provide the multiple-load state for use in a human-robot cooperative task system.

Keywords: Physical Human-Robot Interaction, Telerobotics, Sensor Fusion
Abstract: To have a robot at home might be great fun: it could fetch and carry things. However it remains open how to teach the robot the places it should go to in a manner that is cheap and entertaining for the user. This paper presents an easy-to-use interface that takes the robot on a virtual leash: using the Nintendo Wii Remote the user can go towards target places while pointing at the robot. Using the inbuilt infrared camera and accelerometers and a couple of LEDs on the robot, the robot will follow the user. We show how a Particle Filter and an Interacting Multiple Model (IMM) Kalman can be configured such that simple hand gestures with the Wii make the robot follow the user’s intention. The concept has been implemented on a mobile robot developed within the robotshome project. The robot leash interface has been tested with 12 volunteers who are interested in new technology but have never controlled a robot. The result is that most users could within a few minutes show the robot the first three places in a home environment. Given the little cost of the interface (about 50) the proposed robot leash is a promising human robot interface.

Keywords: Physical Human-Robot Interaction, Cognitive Human-Robot Interaction, Haptics and Haptic Interfaces
Abstract: In this paper it is shown how variation of the kinematic structure of an arm exoskeleton and variation of its fixation pressure on the human limb influences subjectively perceived task performance, such as comfort and the individual indices of the NASA TLX rating scale. It is shown by experimental results that the attachment pressure has a dominant effect on perceived comfort, mental load, physical demand and effort experienced by subjects and is optimal within a range of 10 – 30 mmHg. Furthermore, it is shown that the inclusion of passive compensatory joints inside an exoskeleton’s structure can reduce mental demand during a tracking task. When the outcome of this paper is interpreted in combination with a set of objective performance results that were presented earlier [1], the subjective performance metrics underline the fact that passive compensatory joints paired with an attachment pressure of 20 mmHg increase ergonomics and provide optimal conditions for task performance and comfort.

Keywords: Cooperating Robots, Social Human-Robot Interaction
Abstract: We present a new model for people guidance in urban settings using one or several mobile robots, that overcomes the limitations of existing approaches, which are either tailored to tightly bounded environments, or based on unrealistic human behaviors. Although the robots motion is controlled by means of a standard particle filter formulation, the novelty of our approach resides in how the environment and human and robot motions are modelled. In particular we define a “Discrete-Time-Motion” model, which from one side represents the environment by means of a potential field, that makes it appropriate to deal with open areas, and on the other hand the motion models for people and robots respond to realistic situations, and for instance human behaviors such as “leaving the group” are considered.

Keywords: Medical Robots and Systems, Sensor Fusion
Abstract: In this paper a sensor fusion for pose estimation using optical and inertial data is presented. The proposed algorithm is based on extended Kalman filtering and fuses data from an optical tracking system and an inertial measurement unit. These two redundant sensor systems complement each other well, with the tracking system providing absolute positions and the inertial measurements giving low latency information of derivatives. Models for both sensors are given respecting the different sampling times and latencies. Another key issue is to use information about every landmark, i.e. marker ball, visible for the tracking system, by coupling the two sensor systems tightly together. The algorithm is evaluated in simulation and tested with an experimental hardware platform. The combined sensor system is robust with respect to short time marker occlusions and effectively compensates for latencies in the pose measurements.

Keywords: Medical Robots and Systems, Recognition
Abstract: Wireless capsule endoscopy (WCE) has been gradually applied in hospitals due to its great advantage that it can directly view the entire small bowel in human body compared with traditional endoscopies and other imaging techniques for gastrointestinal diseases. However, a challenging problem with this new technology is that too many images produced by WCE causes a tough task to doctors, so it is very significant to help and relief the clinicians if we can develop computer based automatic detection system to prescreen the collected large amount of images and identify the images with potential problems. In this paper, we propose a new scheme aimed for small bowel tumor detection of WCE images. This new scheme utilizes texture feature, also a powerful clue used by physicians, to detect tumor images with support vector machine. We put forward a new idea of wavelet based local binary pattern as the textural features to discriminate tumor regions from normal regions, which take advantage of wavelet transform and uniform local binary pattern. With support vector machine as the classifier, three-fold cross validation experiments on our present image data verify that it is promising to employ the proposed texture features to recognize the small bowel tumor regions.

Keywords: Medical Robots and Systems, Computer Vision
Abstract: This paper presents a mathematical basis for judging the quality of camera and projector placement in 3D for structured light systems. Two important quality metrics are considered: visibility, which measures how much of the target object is visible; and scale, which measures the error in detecting the visible portions. A novel method for computing each of these metrics is presented. An example is discussed which demonstrates use of these two metrics. The proposed techniques have direct applicability to the task of monitoring patient safety for radiation therapy applications.

Keywords: Medical Robots and Systems, Mechanism Design
Abstract: In recent years, due to the increasing rate of elderly people in Japan, the needs to detect adults’ diseases at the early stage becomes a high priority. In particular, an increased interest in detecting heart and cerebrovascular diseases at an early stage may allow clinicians to begin treatment sooner, when interventions are generally more effective and less expensive. Recently, the Wave Intensity (WI) has been proposed as a new hemodynamic index that provides information about the dynamic behavior of the heart and the vascular system and their interaction. However; the repetitiveness and accuracy of the WI measurement depend on the precision of the positioning of the ultrasound probe. Therefore a positioning device for ultrasound probe is required. Such a device should not only be used to keep the position but also for the fine positioning of the probe. For this purpose, at Waseda University, we have proposed the development of a robot system to assist a carotid blood flow measurement using ultrasound diagnostic equipments. In this paper, the development of Waseda-Tokyo Women’s Medical-Aloka Blood Flow Measurement System No. 1 Refined II (WTA-1RII) is detailed. The system consists of an ultrasound diagnostic device, a 6-DOFs parallel link manipulator, a serial link passive arm, ball joint, and a joystick type controller. The WTA-1RII has improved the design of the gravity compensation mechanism. In addition, a genetic algorithm has by implemented to determine the optimal link’s position of the 6-DOFs parallel manipulator to increase the workspace. Finally, a set of experiments were carried out to determine the usability of the proposed system.

Keywords: Learning and Adaptive Systems, Rehabilitation Robotics, Physical Human-Robot Interaction
Abstract: The multi-DOF prosthetic hand’s myocontrol needs to recognize more hand gestures (or motions) based on myoelectric signals. This paper presents a classification method, which is based on the support vector machine (SVM), to classify 19 different hand gesture modes through electromyographic (EMG) signals acquired from six surface myoelectric electrodes. All hand gestures are based on a 3-DOF configuration, which makes the hand perform like three-fingered. The training performance is very high within each test session, but the cross-session validation is typically low. Acceptable cross-session performance can be achieved by training with more sessions or fewer gesture modes. A fast rhythm muscle contraction is suggested, which can make the training samples more resourceful and improve the prediction accuracy comparing with a relative slow muscle contraction method. For many precise grasp tasks, it is beneficial to the prosthetic hand’s myocontrol if we can efficiently extract the grasp force directly from EMG signals. Through grasping a JR3 6 dimension force/torque sensor, the force signal applying to the sensor can be recorded synchronously with myoelectric signals. This paper uses three methods, local weighted projection regression (LWPR), artificial neural network (ANN) and SVM, to find the best regression relationship between these two kinds of signals. It reveals that the SVM method is better than ANN and LWPR, especially in the case of cross-session validation. Also, the performance of grasping force estimation based on specific hand gestures is superior to the performance of grasping with random fingers.

Keywords: Micro/Nano Robots, Micro-manipulation, Smart Actuators
Abstract: We have investigated an active size controlled droplet generation system by using magnetically driven microtool (MMT). With a lateral motion of the MMT in microchannels, the continuous phase can be pinched off by the movement of MMT to obtain size-controlled droplets actively. With this method, particle-enclosed droplet can be produced on demand to fit the size of each enclosed particle, and which is difficult to carry out only by the fluid dynamic force. For the current study, the system has been evaluated in terms of the frequency of the actuation of MMT and the size of the produced droplets, and found out the response time to change the droplet size by MMT actuation is one third of that only by the fluid dynamic force. This system contributes to the effective transportation of cells in microchannel.

Keywords: Micro/Nano Robots, Micro-manipulation, Cooperating Robots
Abstract: This work presents the control of multiple untethered rectilinear magnetic micro-robots (Mag-uBots) with dimensions 250 X 130 X 100 um³ actuated by pulsed external magnetic fields, which translate by induced stick-slip motion at speeds of up to 4 mm/s immersed in silicone oil. Multiple Mag-uBot control is enabled by employing an array of individually addressable electrostatic surfaces to selectively anchor individual Mag-uBots. Coupled parallel and uncoupled serial motion of multiple robots is demonstrated, and they can combine to form an assembly that is also capable of motion. Manipulation of 230 um diameter microspheres is also demonstrated cooperatively by two Mag-uBots in a fluid environment, and is enhanced when the two Mag-uBots are combined. An analysis of the electrostatic anchoring forces and the forces relevant to manipulation is discussed.

Keywords: Micro/Nano Robots, Motion Control, Medical Robots and Systems
Abstract: This paper reports the use of a MRI device to pull a magnetic microrobot inside a vessel and control its trajectory. The bead subjected to magnetic and hydrodynamic forces is first modeled as a nonlinear control system. Then, a backstepping approach is discussed in order to synthesize a feedback law ensuring the stability along the controlled trajectory. We show that this control law, combined with a high gain observer, provides good tracking performances and robustness to measurement noise as well as to some matched uncertainties.

Keywords: Micro/Nano Robots, Micro-manipulation, Medical Robots and Systems
Abstract: Various types of actuation methods for intravascular locomotive microrobot have been proposed and demonstrated. Among the actuation methods, electromagnetic based actuation (EMA) was considered as a promising mechanism. In generally, planar EMA systems for 2 dimensional movement of the microrobot were proposed and demonstrated. In this paper, we present 3 dimensional (D) EMA systems for the 3D space locomotion of the microrobot. The proposed system consists of a coil system and a robotic actuation system. The coil system has a pair of Helmholtz coils and a pair of Maxwell coils, and the robotic actuation system has a serial robot structure with roll-pitch-roll rotational axes which can rotate about three orthogonal axes (X, Y and Z). Finally, through experiments, we can demonstrate 3D movement of the microrobot by using the proposed EMA system. The proposed EMA system can be utilized for the 3D actuation of the intravascular microrobot.

Keywords: Micro/Nano Robots, Smart Actuators, Medical Robots and Systems
Abstract: Abstract—Our group has previously demonstrated that magnetic nanoparticles (MNP) embedded in microrobots can be used for propulsion and tracking in the human vascular network while being guided by an MRI platform. Here, we show that the same magnetic nanoparticles can also be exploited to perform various functions including but not limited to hyperthermic drug release actuators. Specifically, we synthesized vascular microrobots by embedding MNP in N-isopropylacrylamide (NIPA) thermo responsive hydrogel. We experimentally demonstrate the decrease in volume of the hydrogel microrobot in response to AC magnetic heating, a property that allows microrobots to adapt to blood vessels of various diameters. This type of hydrogel is not only able to reduce size in response to temperature elevations but it can also be used to release possible therapeutic agents previously trapped within the hydrogel. Here, NIPA hydrogel samples were placed inside an AC magnetic field of 116 Oe at 145 kHz. Temperature elevations as well as change in hydrogel volume were recorded.

Keywords: Sensor Networks, Localization, Sensor Fusion
Abstract: Indoor location tracking of mobile robots or transport vehicles using wireless technology is attractive for many applications. IEEE 802.15.4a wireless networks offer an inexpensive facility for localizing mobile devices by time-based range measurements. The main problems of time-based range measurements in indoor environments are errors by multipath and non-line-of-sight (NLOS) signal propagation. This paper describes indoor tracking using range measurements and an Extended Kalman Filter with NLOS mitigation. The commercially available nanoLOC wireless network is utilized for range measurements. The paper presents experimental results of tracking a forklift truck in an industrial environment.

Keywords: Sensor Fusion, Navigation, Localization
Abstract: Bio-logging is a new interdisciplinary research area at the intersection of animal behavior and bioengineering. It involves several applications such as determination of specific parameters (attitude, acceleration, and position) via a new generation of Mechatronic systems. The aim of this paper concerns the animal motion estimation problem using low-cost sensors fusion. A quaternion-based nonlinear observer for the tracking of rigid body attitude (orientation) and heading using measurements provided from low cost inertial and magnetic sensors is presented. The algorithm combines low-frequency, 3-axis accelerometer and 3-axis magnetometer, data with high frequency 3-axis gyroscope measurement. Then, to increase the performance and reduce the computational requirements, we exploit the sensor readings directly in the designed observer. Using the estimated attitude, the linear acceleration is then derived. This latter will be used in the future to evaluate the animal energy index and its mechanical work. Finally, some experimental results, using the measurements provided by an inertial sensor put on dog are given to illustrate the efficiency of the proposed algorithm.

Keywords: Sensor Networks, Networked Robots
Abstract: This paper presents a distributed algorithm for a mobile sensor network to track targets with unknown motion. We formulates the target tracking as a multi-objective optimization problem which integrates the tracking quality, the energy saving and the network connectivity. To cope with sensing noises, we use the determinant of the covariance matrix of target estimation as the tracking quality measure and compute its partial derivatives for the optimization process. Virtual nodes are introduced to represent obstacles in the environment. Furthermore this algorithm can be extended to solve the problem of source tracking where sensors can only detect the density of the diffusing substances emitted by the source. Therefore a whole tracking framework has been set up which can be easily extended for applications under complicated situations. Simulations demonstrate the effectiveness of the proposed algorithm in energy conservation and tracking accuracy under different situations.

Keywords: Sensor Networks, Field Robots, Mapping
Abstract: Gas distribution modelling constitutes an ideal application area for mobile robots, which – as intelligent mobile gas sensors – offer several advantages compared to stationary sensor networks. In this paper we propose the Kernel DM+V algorithm to learn a statistical 2-d gas distribution model from a sequence of localized gas sensor measurements. The algorithm does not make strong assumptions about the sensing locations and can thus be applied on a mobile robot that is not primarily used for gas distribution monitoring, and also in the case of stationary measurements. Kernel DM+V treats distribution modelling as a density estimation problem. In contrast to most previous approaches, it models the variance in addition to the distribution mean. Estimating the predictive variance entails a significant improvement for gas distribution modelling since it allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. Estimating the predictive variance also provides the means to learn meta parameters and to suggest new measurement locations based on the current model. We derive the Kernel DM+V algorithm and present a method for learning the hyper-parameters. Based on real world data collected with a mobile robot we demonstrate the consistency of the obtained maps and present a quantitative comparison, in terms of the data likelihood of unseen samples, with an alternative approach that estimates the predictive variance.

Keywords: Micro-manipulation, Force and Tactile Sensing, Haptics and Haptic Interfaces
Abstract: In 2D microassembly applications, it is inevitable to position and orient polygonal micro-objects lying on a flat surface. Point contact pushing of micro-objects provides a feasible way to achieve the task and it is more flexible and less complex compared to pick and place operation. Due to the fact that in micro-world surface forces are much more dominant than inertial forces, and tend to be unevenly distributed, these dominant forces obstruct the desired motion of the micro-object when using point contact pushing alone. Thus by adopting an hybrid vision/force feedback scheme, it is possible to attain a translation motion of the object as the uncertainties due to varying surface forces and disorientation of the micro-object is compensated by force and vision feedback respectively. In this paper, a hybrid vision/force feedback scheme is proposed to push micro-objects with human assistance using a custom built tele-micromanipulation setup to achieve translational motion. The pushing operation is divided into two concurrent processes: In one human operator acts as an impedance controller alters the velocity of the pusher while in contact with the micro-object through scaled bilateral teleoperation to compensate for varying surface forces. In the other process, the desired line of pushing for the micro-object is determined continuously using visual feedback procedures so that it always compensate for the disorientation. Experimental results are demonstrated to prove nano-Newton range force sensing, scaled bilateral teleoperation with force feedback and pushing micro-objects.

Keywords: Biologically-Inspired Robots, Search and Rescue Robots, Space Robotics
Abstract: In nature, many animals are able to jump, upright themselves after landing and jump again. This allows them to move in unstructured and rough terrain. As a further development of our previously presented 7g jumping robot, we consider various mechanisms enabling it to recover and upright after landing and jump again. After a weighted evaluation of these different solutions, we present a spherical system with a mass of 9.8g and a diameter of 12cm that is able to jump, upright itself after landing and jump again. In order to do so autonomously, it has a control unit and sensors to detect its orientation and spring charging state. With its current configuration it can overcome obstacles of 76cm at a take-off angle of 75°.

Keywords: Evolutionary Robotics, Biologically-Inspired Robots, Legged Robots
Abstract: In this paper we present a concept and an evaluation of an ape-like robot which is quite similar to its biological model. Aim of our project LittleApe is to build a small and extreme lightweight robot that is capable of walking on two and four legs as well as of changing from a four-legged posture to a two-legged posture, manipulating small objects, and which is also able to climb. LittleApe is modelled with attributes of a chimpanzee regarding limb proportions, spinal column, centre of mass, walking pattern, and range of motion.

The concept of LittleApe is tested in simulation while building the real system. Two aspects were chosen to evaluate the concept described in detail within this paper. The first aspect comprises the use of an evolutionary method and the comparison of different morphologies. Based on the results from the first one, the second aspect deals with the manoeuvrability of the LittleApe robot.

Keywords: Biologically-Inspired Robots, Biomimetics
Abstract: One of the prominent challenges in mobile robotics is to develop control methodologies that allow the adaptation to dynamic and unforeseen environments. The classic approach of hand-coded controllers is very efficient for well-defined tasks and specific environments but poor in adapting to changing environmental conditions. One alternative approach is the application of evolutionary algorithms which need, in turn, easily evolvable representations of controllers. In this paper, we investigate one promising approach of an artificial hormone system as a control paradigm which is believed to be easily optimized by evolutionary processes. In a first step of this research, we focus on the simple task of collision avoidance. We present a brief mathematical analysis of this controller approach and an implementation of the controller on a mobile robot to check the feasibility in principle of our approach. The task is successfully accomplished and we conclude with a discussion of the hormone dynamics in the robot.

Keywords: Biologically-Inspired Robots, Agent-Based Systems
Abstract: We describe a simple controller for swarms of foraging robots that reduces mutual spatial interference and adapts to non-uniform resource distributions. We discuss several sources of such non-uniformity, and show that some non-uniform distributions are not well-handled by previously described foraging schemes. Our new method adapts each robot's work site size and location during run time, to reflect the distribution encountered. The controller is very scalable, using only local information and no explicit communication. Simulation studies demonstrate the method's effectiveness.

Keywords: Biologically-Inspired Robots, Flexible Arms, Biomimetics
Abstract: Robots have become an integral part of human life, and the relationship between humans and robots has grown closer. Thus, it is desired that robots have characteristics similar to humans. In this context, we paid attention to an artificial muscle actuator. We used straight-fiber-type artificial muscles, derived from the McKibben type, which have excellent characteristics with respect to the contraction rate and force. We developed a 6-DOF manipulator actuated by a straight fiber artificial muscle. Furthermore, we tried to control the manipulator position by considering its characteristics.

Keywords: Mechanism Design, Motion Control, Smart Actuators
Abstract: Abstract—A capsule robot that moves utilizing the internal force between the shell and the sliding mass and the friction between the shell and the environment is named “internal force-static friction” capsubot. The new driving mode is used in the active gastrointestinal examination robot system, which is a novel and meaningful attempt. In this paper, for the operation mechanism and movement characteristics of capsubot, a new type of electromagnetic driver has been designed. The driver is optimized and analyzed by magnetic circuit method and finite element method. Then we manufacture the prototype of the capsubot. The driver has big output power, a small size and a high weight proportion of the sliding mass and the shell, which has been proved by the experiment. The speed on the table is 45.8mm/s.

Keywords: Mechanism Design, Search and Rescue Robots, Motion Control
Abstract: We introduce a unique shaped crawler robot aimed for high-step climbing that is considered the most necessary ability in urban search and rescue operations. The crawler robot is composed of two triangular-shaped crawler devices connected by a center shaft, a straight crawler device and a two-link mechanism connecting the shaft and the straight crawler. The robot is very compact and lightweight compared to other rescue robots. It has eight D.O.F. in total, four of which are for crawlers and the others are for shifting the shape of the robot. We confirmed that the proposed robot can get over 36 cm high-step one-and-a-half times as high as its original height. We also implemented a height-independent climbing motion algorithm based on statics and geometrical analysis in climbing process. Various hardware experiments showed a capability of the developed robot and feasibility of the proposed motion algorithm.

Keywords: Legged Robots, Biologically-Inspired Robots, Motion Control
Abstract: A hexapod designed for wall climbing with a body joint and six 3-DOF legs can perform complex maneuvers such as sharp turns, making both interior and exterior transitions between vertical and horizontal surfaces, and traversing obstacles on both surfaces. This paper presents work toward the design and construction of the hexapod DIGbot, named for its utilization of Distributed Inward Gripping (DIG) to generate adhesive forces. The biologically-inspired DIG approach allows robots to climb on surfaces of any orientation with respect gravity, including ceilings, or in zero gravity environments.

Keywords: Legged Robots, Biologically-Inspired Robots, Motion Control
Abstract: Traditional legged runners and climbers have relied heavily on gait generators in the form of internal clocks or reference trajectories. In contrast, here we present physical experiments with a fast, dynamical, vertical wall climbing robot accompanying a stability proof for the controller that generates it without any need for an additional internal clock or reference signal. Specifically, we show that this ``self-exciting'' controller does indeed generate an ``almost'' globally asymptotically stable limit cycle: the attractor basin is as large as topologically possible and includes all the state space excluding a set with empty interior. We offer an empirical comparison of the resulting climbing behavior to that achieved by a more conventional clock-generated gait trajectory tracker. The new, self-exciting gait generator exhibits a marked improvement in vertical climbing speed, in fact setting a new benchmark in dynamic climbing by achieving a vertical speed of 1.5 body lengths per second.

Keywords: Mechanism Design, Underactuated Robots
Abstract: This paper presents a tracked robot composed of the proposed crawler mechanism, in which a planetary gear reducer is employed as the transmission device and provides two outputs in different forms with only one actuator. When the crawler moves in a rough environment, collision between mechanism and environment inevitably occurs. This underactuated crawler can absorb the impact energy that should be transmitted to the actuator. A modular concept for the crawler is proposed for enlarging its use in robot systems and mechanical design of a modular crawler is conducted. Using this crawler module, a four-crawler-driven robot is realized by easily assembling. Experiments are conducted to verify the proposed concept and mechanical design. A single crawler module can well perform the proposed three locomotion modes. The four-crawler-driven robot has good adaptability to the environment which can get over obstacles both passively and actively.

Keywords: Dynamics, Legged Robots, Biologically-Inspired Robots
Abstract: A quadrupedal water runner robot inspired by the basilisk lizard has previously demonstrated the capability of water surface locomotion. Since the robot is aimed for the amphibious locomotion, a compatible design on both ground and water surface is discussed in this paper. A compliant footpad which can transfer elastic energy to propulsive momentum is introduced and modeled using a pseudo-rigid-body model. Dynamic modeling of the footpad and the robot provides a criterion of efficient ground locomotion. For the water surface locomotion, drag force can be reduced by compliance of the footpad. The optimized design taking into account two locomotions is studied and analyzed for stability using the Poincare map.

Keywords: Sensor Fusion, Voice, Speech Synthesis and Recognition, Computer Vision
Abstract: In mobile robotics applications, pattern and object recognition are mainly achieved relying only on vision. Several other perceptual modalities are also available such as, touch, hearing or vestibular proprioception. They are rarely used and can provide valuable additional information within the recognition tasks. This article presents an analysis of several methods of fusion of perceptual and auditory modalitites. It relies on the use of a perspective camera and a microphone on a moving object recognition problem. Experimental data are also provided on a database of audio/visual objects including cases of visual occlusions and audio corruptions.

Keywords: Voice, Speech Synthesis and Recognition, Learning and Adaptive Systems
Abstract: The speech enhancement architecture presented in this paper is specifically developed for hands-free robot spoken dialog systems. It is designed to take advantage of additional sensors installed inside the robot to record the internal noises. First a modified frequency domain blind signal separation (FD-BSS) gives estimates of the noises generated outside and inside of the robot. Then these noises are canceled from the acquired speech by a multichannel Wiener post-filter. Some experimental results show the recognition improvement for a dictation task in presence of both diffuse background noise and internal noises.

Keywords: Localization, Cognitive Human-Robot Interaction, Voice, Speech Synthesis and Recognition
Abstract: As robotic technology plays an increasing role in human lives, “robot audition”, human-robot communication, is of great interest, and robot audition needs to be robust and adaptable for dynamic environments. This paper addresses sound source localization working in dynamic environments for robots. Previously, noise robustness and dynamic localized sound selection have been enormous issues for practical use. To correct the issues, a new localization system “Selective Attention System” is proposed. The system has four new functions: localization with Generalized EigenValue Decomposition of correlation matrices for noise robustness(“Localization with GEVD”), sound source cancellation and focus (“Target Source Selection”), human-like dynamic Focus of Attention (“Dynamic FoA”), and correlation matrix estimation for robotic head rotation (“Correlation Matrix Estimation”). All are achieved by the dynamic design of correlation matrices. The system is implemented into a humanoid robot, and the experimental validation is successfully verified even when the robot microphones move dynamically.

Keywords: Sensor Networks, Voice, Speech Synthesis and Recognition
Abstract: This paper presents the Embedded Audition for Robotics (EAR) project internally developed at LAAS and its application to speaker localization and extraction. Hardware and software issues are first thoroughly depicted, concerning the development of an auditory sensor based on an array of microphones, a homemade dedicated acquisition chain and a FPGA based processing board. Then, the EAR sensor is assessed against various scenarios, in real noisy robotics environments. Localization results are presented when a speaker emits an utterance in the presence of a disturbing source. These validate the underlying theory and suggest further theoretical and experimental developments.

Keywords: Voice, Speech Synthesis and Recognition, Cognitive Human-Robot Interaction, Medical Robots and Systems
Abstract: This paper proposes real-time sound source orientation estimation based on orientation-extended amplitude beamforming (OE-ABF). To recognize a sound source orientation (such as face orientation) is an important function for a robot who can achieve natural human-robot interaction because the function is required to distinguish the human target from a robot or another person. We developed a sound source orientation system using orientation-extended beamforming (OE-BF) and showed the system worked properly at least under a specific controlled environment. However, in practical use, this system does not work properly because the system doesn't take into account the differences between the supposed model in OE-BF and in practical situations. For example, the system model supposes that there is neither noise nor reverberation, however, this is not a realistic assumption. To solve this assumption mismatch problem, we propose sound source orientation estimation based on OE-ABF, and constructed a real-time sound source orientation estimation system with the proposed method using a 96ch microphone array. Evaluation results of our proposed system show that the average error of estimated angles is lower than 5^circ, while the error of our previously reported system was greater than 20^circ. With this system, the robot is able to distinguish that the utterance target of a person standing 1m in front is itself or another person standing 0.2m to the left of the robot. This is valuable for human-robot interaction.

Keywords: Autonomous Agents, Computer Vision, Aerial Robotics
Abstract: Autonomous navigation of an unmanned aerial vehicle (UAV) can be achieved with a reactive system which allows the robot to overcome all the unexpected changes in its environment. In this article, we propose a new approach to avoid frontal obstacles using known properties of the optical flow and by taking advantage of the capability of stationary flight of the rotorcraft. A state machine is proposed as a solution to equip the UAV with all reactions necessary for indoor navigation. We show how smooth transitions can be achieved by decreasing the speed of the vehicle proportional to the distance to an obstacle and by brief instants of stationary flight. Each stage of our algorithm has been tested in a mobile robot.

Keywords: Autonomous Agents, Behaviour-Based Systems, Navigation
Abstract: This paper presents a novel approach to behavior based control of mobile robots using supervisory control of Fuzzy Discrete Event Systems (FDES). Fuzzy events are triggered by the sensor readings and the inference occurs through a fuzzy rule base system. The supervisor can activate and control fuzzy controllable events simultaneously with fuzzy uncontrollable events to achieve the planned objectives. The fuzzy observability concept is incorporated to represent sensor uncertainties. Fuzzy state based controllability and observability measures are also discussed. The proposed theoretical development is then extended to discuss an application with behavior based control of mobile robots.

Keywords: Autonomous Agents, Navigation, Field Robots
Abstract: Autonomous mobile robots are deployed in a variety of application domains, resulting in scenario specific implementations. However these systems share common components responsible for perception, path planning and task execution. In order to find a formal way to identify the influence of the environmental complexity to the used methods, an approach for quantitative system interdependence analysis is introduced. The coherence between several performance indicators of different system components, as well as the influence of environmental parameters on the system, are learned and quantitatively evaluated. Performance evaluation of an autonomous robot navigating in two different urban environments is conducted and presented results demonstrate the applicability of the proposed approach.

Keywords: Autonomous Agents, Gesture, Posture, Social Spaces and Facial Expressions, Motion Control
Abstract: A formal notion of gesturing defined as the modulation of relative separation between mobile robots has been explored in "Dhananjay Raghunathan and John Baillieul, Exploiting information content in relative motion, Americal Control Conference, June 2009". We extend this work by developing a peer-to-peer communication channel and an associated distributed communication protocol based exclusively on modulating relative motion and observing it. Protocols that enable two Dubins vehicles modulating their relative separation in the plane to effectively exchange information, as well as nonlinear control laws that enable these protocols are presented. Only local information is assumed for the control action. We illustrate the contextual nature of such signaling by showing applications to secure communication as well as robot formation motion. Simulations are presented to validate the work.

Keywords: Autonomous Agents, Aerial Robotics, Search and Rescue Robots
Abstract: In the priority search phase of Wilderness Search and Rescue, a probability distribution map is created. Areas with higher probabilities are searched first in order to find the missing person in the shortest expected time. When using a UAV to support search, the onboard video camera should cover as much of the important areas as possible within a set time. We explore several algorithms (with and without set destination) and describe some novel techniques in solving this problem and compare their performances against typical WiSAR scenarios. This problem is NP-hard, but our algorithms yield high quality solutions that approximate the optimal solution, making efficient use of the limited UAV flying time.

Keywords: Calibration and Identification
Abstract: This paper describes an industrial robot joint offset calibration method called the virtual line-based single-point constraint approach. Previous methods such as using CMM, laser trackers or cameras are limited by the cost or the resolution. The proposed method relies mainly upon a laser pointer attached on the end-effector and single position-sensitive detector (PSD) arbitrarily located on the workcell. The automated calibration procedure (about three minutes) involves aiming the laser lines loaded by the robot towards the center of the PSD surface from various robot positions and orientations. The intersections of each pair of laser lines eventually should converge to the same point after compensating the joint offsets. An optimization model and algorithm have been formulated to identify the robot offset. For the highly precise feedback, a segmented PSD with a position resolution of better than 0.1 μm is employed. The mean accuracy of robot localization is up to 0.02 , and the mean error of the parameter identification is less than 0.08 degrees. Both simulations and experiments implemented on an ABB industrial robot verify the feasibility of the proposed method and demonstrated the effectiveness of the developed calibration system. The goal of fast, automated, low-cost, and high precision offset calibration are achieved.

Keywords: Range Sensing, Computer Vision, Calibration and Identification
Abstract: The objective of this paper is to propose a windshield surface shape and optical parameters inspection system. In this paper, a white board works as a diffuse planar light source projecting structured light patterns because physical properties of specular surface do not allow us to directly apply the triangulation-based techniques used in ordinary diffuse surface inspection. The board is placed at two different positions and the distorted structured light patterns are observed by a fixed camera so that the incident vector for every point on the windshield surface is determined using corresponding points in the board at two different positions. Likewise, the reflection vector is determined by camera calibration. Hence, the 3D shape and normal of the windshield surface are obtained by the intersection of the incident and reflection vectors. The normal of the surface denotes the optical reflective property of the windshield. Last, accuracy and consistence experiments are conducted. The experiment results demonstrate the efficiency and accuracy of our system.

Keywords: Service Robots, Intelligent Vehicles, Motion Control
Abstract: In this paper, the problem of providing flexible process integration for Mass Customisation Manufacturing is addressed. A subset of the total distributed process integration is assumed to be handled by flexible routing operations. Physical routing operations are considered to be facilitated by autonomous mobile Payload Routing Platforms (PRP's). Facility layout flexibility is extended through active material routing operations. A prototype mobile PRP is presented, which has been developed for preliminary testing and validation of the motion control associated with providing distributed process integration under customer-induced production dynamics.

Keywords: Neural and Fuzzy Control, Intelligent Vehicles
Abstract: In this paper the design and development of a crawling robot for inspection of live water pipes are addressed. The mechanical design of the robot is described in detail. The governing dynamics equations of the robot moving against water flow as well as gravity in a straight pipe are also derived. Specifically, the hydrodynamic forces exerted on the robot when moving in a live pressurized pipe are taken into account. Two fuzzy-logic based control strategies are adopted. The first one is to maintain a constant translational speed in robot’s motion when subjected to flow disturbances that are numerically modeled using step changes in flow velocity within a human-in-the-loop real-time simulation environment, and the second is to steer the real robot inside the pipe while following a numerically modeled time-varying velocity set point with no fluid present in the pipe. The controller parameters were tuned based on data obtained from a human-in-the-loop control system via an artificial neural network.

Keywords: Parallel Robots, Mechanism Design, Robotics in Construction
Abstract: This paper proposes a new spatial 3-DOF parallel mechanism with a unique forward kinematic solution. Using the Scott mechanism as its sub-chain, the mechanism is foldable, which is useful for design of a compact-sized master device. The kinematics of this mechanism is derived and its kinematic characteristics are analyzed in terms of workspace and kinematic isotropy. The mechanism was implemented and tested as a master device to control a virtual construction robot handling a large glass plate.

Keywords: Mechanism Design, Control Architectures and Programming
Abstract: Proportional-Integral-Derivative (PID) control is widely used to control mechanical systems. In PID control technique, however, there are limits to the accuracy of the resulting movement because of the influence of gravity, friction,and interaction of joints caused by modeling errors. Digital acceleration control has robustness for the modeling errors. But it requires position, velocity, and acceleration of a controlled object to construct a controller. In this paper, we use the novel digital differentiator, ESDS. It enables digital acceleration control without increasing the number of sensors. Furthermore, the proposed method works effectively for quantized sensor data. The validity of the proposed method is confirmed by simulations and experiments using 2-link manipulator.

Keywords: Micro-manipulation, Micro/Nano Robots, Parallel Robots
Abstract: In this paper, a global sliding mode control (GSMC) scheme is implemented on a piezo-driven XY parallel micropositioning stage to compensate for the unmodeled hysteresis aiming at a sub-micron accuracy motion tracking control. The GSMC controller is designed with the consideration of all uncertainty bounds. In the controller implementation, a high-gain velocity observer is adopted to estimate the feedback velocity from the measured position. The effectiveness of the GSMC over ordinary SMC and traditional PID control is demonstrated through simulations, while the variations of design parameters on control performances are examined as well. Results show that the GSMC can reduce the hysteresis to a negligible level and lead to a sub-micron accuracy tracking with tolerance to some degrees of external disturbances, which provides a sound base for practical control of the micropositioning system for micro/nano scale manipulation.

Keywords: Micro-manipulation, Micro/Nano Robots
Abstract: Three-dimensional (3-D) automated micromanipulation at scale of several micrometers using a nanotip gripper is presented. The gripper is constructed from protrudent tips of two independently actuated atomic force microscope (AFM) cantilevers and each cantilever. A protocol allows these two cantilevers to form a gripper for grasping and releasing the microspheres to target positions without obstacle of adhesive forces in air. For grasping, amplitude feedback from the dithering cantilevers is employed to locate the grasping points by laterally scanning the side of the microspheres. Real time force sensing is used to monitor the whole process of the pick-and-place with steps of pickup, transport and release. For trajectory planning, an algorithm based on the shortest path solution is used to obtained 3-D micropatterns with high efficiencies. In experiments, microspheres with diameters from 3 μm to 4 μm were manipulated and 3-D micropyramids with two layers were achieved. 3-D micromanipulation and 3-D microassembly at the scale of several microns to submicron could become feasible through the newly developed nanotip gripper.

Keywords: Micro/Nano Robots, Smart Actuators, Micro-manipulation
Abstract: Piezoelectric cantilevers have proved their performances for actuating microgrippers dedicated to micromanipulation and microassembly tasks. While the control of one degree-of-freedom (dof) piezocantilevers have been well whelmed, the control of multi-dof one has not been addressed. Indeed, to assemble complex structures, the use of multi-dof microgrippers is recognized. Unfortunately, strong coupling between the axis and nonlinearities indeniably limit their performances.

This paper deals with the modeling and control of a piezocantilever that has 2 degrees of freedom: in-plane and out of plane deflections. While such a characteristic allows the microgrippers perform both orientation and translation during micromanipulation/microassembly tasks, the strong coupling between the two dof makes difficult their control. Moreover, nonlinearities (hysteresis and creep) raise when the piezocantilever is used in high deformation. To overcome these, we consider the coupling as a disturbance, model the nonlinearities with the quadrilateral approximation and we apply a robust H_inf controller that accounts them. The experiments show the efficiency of the synthesized controller and the obtained performances are convenient for micromanipulation/microassembly tasks.

Keywords: Micro-manipulation, Parallel Robots, Motion Control
Abstract: In recent years, many applications in precision engineering require a careful isolation of the instrument from the vibration sources by adopting active vibration isolation system to achieve a very low remaining vibration level especially for the very low frequency under 10Hz vibration signals. In this paper, based on the previous research experiences in the systematical modeling and study of parallel robots, a hybrid robot is described and the vibration model is given by using Lagrange's Equations. Then the present study addresses the issues related to the active vibration control schemes for the MIMO system using LQR algorithm. Finally, numerical simulations on the effect of active vibration control are presented.

Keywords: Path Planning for Manipulators, Motion Control, Dynamics
Abstract: Abstract— This paper presents a mechanism and a control strategy that enables automated non-contact manipulation of spherical objects in three dimensions using air flow, and demonstrates several tasks that can be performed with such a system. The mechanism is a 2-DOF gimbaled air jet with a variable flow rate. The control strategy is feedback linearization based on a classical fluid dynamics model with state estimates from stereo vision data. The tasks include palletizing, sorting, and ballistics. All results are verified with hardware experiments.

Keywords: Path Planning for Manipulators, Contact Modelling, Dynamics
Abstract: In this paper, we propose the use of complementarity-based dynamic simulation algorithms for kinodynamic motion planning. Dynamic simulation algorithms are used as local planning methods in sampling-based motion planning algorithms to find inputs that ensure the resulting trajectory satisfies the dynamics constraints. However, the inputs are not guaranteed to give collision-free path segments. The inputs, chosen either by random sampling or from a discretization of the available inputs, are rejected if the path segment is not collision free. In cluttered environments, finding a feasible input is difficult and sensitive to the duration of application of the input, Delta t, and to the discretization resolution of the input set. When the collision constraints (or any inequality constraints on the state of the robot) are modeled as a set of complementarity constraints, the dynamic simulation algorithm gives a path segment that touches the obstacles and a set of {em contact forces} whenever the robots make contact with the obstacles. The sum of the original chosen input forces and the contact forces transformed to the input space gives a control input that guarantees a collision free path segment (provided it is within the actuator bounds). Thus in cluttered environments, using a complementarity-based dynamic simulation algorithm, we can find a feasible input that is relatively insensitive to the choice of Delta t and the discretization resolution of the input set. We present preliminary simulation examples showing the advantages of our algorithm in cluttered environments.

Keywords: Path Planning for Manipulators, Robotics in Agriculture and Forestry, Redundant Robots
Abstract: We consider trajectory planning for kinematically redundant manipulators used on forestry machines. The analysis of recorded data from human operation reveals that the driver does not use the full potential of the machine due to the complexity of the manipulation task. We suggest an optimization procedure that takes advantage of the kinematic redundancy so that time-efficient joint and velocity profiles along the path can be obtained. Differential constraints imposed by the manipulator dynamics are accounted for by employing a phase-plane technique for admissible path timings. Velocity constraints of the individual joints are particularly restrictive in hydraulic manipulators. Our study aims for semi-autonomous schemes that can provide assistance to the operator for executing global motions.

Keywords: Path Planning for Manipulators, Medical Robots and Systems
Abstract: An active cannula is a medical device composed of thin, pre-curved, telescoping tubes that may enable many new surgical procedures. Planning optimal motions for these devices is challenging due to their kinematics, which involve both beam mechanics and space curves. In this paper, we propose an optimization-based motion planning algorithm that computes actions to guide the device to a target point while avoiding obstacles in the environment. The planner uses a simplified active cannula kinematic model that neglects beam mechanics, and focuses on planning for the (piecewise circular) space curves. The method is intended for use in image-guided procedures where the target and obstacles can be segmented from pre-procedure images. Given the target location, the start position and orientation, and a geometric representation of obstacles, the algorithm computes the insertion length and orientation angle for each tube of the active cannula such that the device follows a collision-free path to the target. We formulate the planning problem as a constrained nonlinear optimization problem and use a penalty method to convert this formulation into a sequence of more easily solvable unconstrained optimization problems. Simulations demonstrate optimal paths for a 3-tube active cannula with spherical obstacles. The algorithm typically computes plans in less than 1 minute on a standard PC.

Keywords: Path Planning for Manipulators, Redundant Robots, Motion Control
Abstract: A work cell is generally designed to achieve a high throughput and its size is typically viewed as contingent to component sizes. In this paper, we aim to design a compact work cell (spatial requirement) and to minimize its task completion time (temporal requirement) to a value set as a constraint. By doing so, the work cell occupies a minimal space and achieves its desired throughput. The work cell size is evaluated based on the size and the swept volume of components. This evaluation is important since a robot arm can have a very large swept volume depending on a given task. To satisfy the spatial and temporal requirements, we propose the integration of the base placement optimization, goal rearrangement, and motion coordination between the robot arm and the positioning table. Furthermore, we introduce two motion coordination schemes based on the spatial and temporal requirements. We showed the effectiveness of the proposed method through simulations.

Keywords: Legged Robots, Dynamics, Force Control
Abstract: Many critical elements for statically stable walking for legged robots have been known for a long time, including stability criteria based on support polygons, good foothold selection, recovery strategies to name a few. All these criteria have to be accounted for in the planning as well as the control phase.

Most legged robots usually employ high gain position control, which means that it is crucially important that the planned reference trajectories are a good match for the actual terrain, and that tracking is accurate. Such an approach leads to conservative controllers, i.e. relatively low speed, ground speed matching, etc. Not surprisingly such controllers are not very robust -- they are not suited for the real world use outside of the laboratory where the knowledge of the world is limited and error prone. Thus, to achieve robust robotic locomotion in the archetypical domain of legged systems, namely complex rough terrain, where the size of the obstacles are in the order of leg length, additional elements are required. A possible solution to improve the robustness of legged locomotion is to maximize the compliance of the controller. While compliance is trivially achieved by reduced feedback gains, for terrain requiring precise foot placement (e.g. climbing rocks, walking over pegs or cracks) compliance cannot be introduced at the cost of inferior tracking. Thus, model-based control and -- in contrast to passive dynamic walkers -- active balance control is required.

To achieve these objectives, in this paper we add two crucial elements to legged locomotion, i.e., floating-base inverse dynamics control and predictive force control, and we show that these elements increase robustness in face of unknown and unanticipated perturbations (e.g. obstacles). Furthermore, we introduce a novel line-based COG trajectory planner, which yields a simpler algorithm than traditional polygon based methods and creates the appropriate input to our control system. We show results from both simulation and real world of a robotic dog walking over non-perceived obstacles and rocky terrain. The results prove the effectivity of the inverse dynamics/force controller. The presented results show that we have all elements needed for robust all-terrain locomotion, which should also generalize to other legged systems, e.g., humanoid robots.

Keywords: Legged Robots, Behaviour-Based Systems, Motion Control
Abstract: The behavior control method was usually adapted for controlling the suspension configuration which determines the traversability of the UGV with actively articulated suspension. In this paper, we proposed a method of configuration planning of the suspension without any detail geometric data of terrain. The terrain was estimated by the traces of each wheel and the behavior plans for the desired upper level behavior were set up against the constraints of the terrain. Also, an optimal suspension configuration was calculated based on the quasi-static stability and power consumption, and plans for the suspension behavior were made. Validity of the proposed method was checked by simulation using some off-the-shelf programs, and showed that the behavior planning without geometric features of terrain and simplification of the behavior planning for obstacle negotiation were possible.

Keywords: Legged Robots, Humanoid Robots
Abstract: Although there have been much research on robot walking, the energy efficiency of central pattern generator (CPG)-based walking has not received much attention. This study proposes a novel method for acquiring energy-efficient CPG-based bipedal walking for a robot with knees and feet. In this method, we introduce a torque-free period for swing leg control into the swing leg control cycle. During this period, no torque is applied to the hip joint controller, and therefore no energy is consumed. When and for how long the torque-free period is inserted into the swing leg control cycle is adaptively acquired by reinforcement learning. Simulation experiments demonstrate the feasibility of our method. The energy consumed in acquiring walking is reduced by 40% compared with simple CPG-based walking without the torque-free period in the practical learning speed. Walking stability is maintained with respect to external disturbances on a level floor. Although the method is more unstable on slopes with the torque-free period, the torque-free-period can be adaptively eliminated to achieve stable walking on the slopes.

Keywords: Behaviour-Based Systems, Personal Robots, Recognition
Abstract: In this paper, we aim to study and classify gait patterns among flat walking, descending stairs, and ascending stairs using inertial measurement unit (IMU) including triaxial accelerometers and gyroscopes. Six subjects were invited to gather gait data of flat walking, descending stairs, and ascending stairs wearing the shoe-integrated system with free speeds. The design of the classifier for identifying gait patterns based on continuous kinematic signals is composed of three steps. In the first step, we separate gait signals of the six sensors in the same period into gait segments which are further used as the units for pattern feature analysis. Secondly, based on discrete wavelet transform (DWT), the average sum of squares of wavelet coefficients of each segment for anteroposterior acceleration, vertical acceleration, and sagittal plane angular rate are demonstrated and selected as the common features for gait pattern classification. At the last step, the fuzzy logic based classifier is proposed according to the distribution of the common features of different gait patterns. Experimental results demonstrate the proposed methodology is efficient for classifying gait patterns during humans’ daily activity.

Keywords: Kinematics, Redundant Robots
Abstract: Snake robots have many degree of freedom. This makes them both extremely versatile and complex to control. In this paper, we address this complexity by introducing two algorithms. Annealed chain fitting efficiently maps a continuous backbone curve to a set of joint angles for a snake robot. Keyframe wave extraction takes joint angles fit to a sequence of backbone curves, and identifies parameterized functions which produce those sequences. We validate the algorithms by using them to produce rolling gaits for crawling and climbing.

Keywords: Localization, Networked Robots, Social Human-Robot Interaction
Abstract: Robust localization of robots and reliable tracking of people are both critical requirements for the deployment of service robots in real-world environments. In crowded public spaces, occlusions can impede localization using on-board sensors. At the same time, teams of service robots working together need to share the locations of people and other robots on the same global coordinate system in order to provide services efficiently. To solve this problem, our approach is to use an infrastructure of sensors embedded in the environment to provide an inertial reference frame and wide-area coverage. Based on a people-tracking system we have previously established which uses laser range finders to track people's trajectories, we have developed a technique to localize a team of service robots on a shared global coordinate system. Each robot's odometry data is associated with the observed trajectory of an entity detected by the laser tracking system, and Kalman filters are used to correct rotational offsets between the robots' individual coordinate systems and the global reference frame. We present our data association and pose correction algorithms and show results demonstrating the performance of our system in a shopping arcade.

Keywords: Sensor Networks, Localization, Surveillance Systems
Abstract: Tracking in sensor networks has shown great potentials in many real world surveillance and emergency system. Due to the distributive nature and unpredictable topology structure of the randomly distributed sensor network, a good tracking algorithm must be able to aggregate large amounts of data from various unknown sources. In this paper, a distributive tracking algorithm is developed using a Markov random field (MRF) model to solve this problem. The Markov random field (MRF) utilizes probability distribution and conditional independency to identify the most relevant data from the less important data. The algorithm converts the randomly distributed network into a regularly distributed topology structure using cliques. This makes tracking in the randomly distributed network topology simple and more predictable. Simulation demonstrate that the algorithm performs well for various sensor field setting, and for various target sizes.

Keywords: Localization, Sensor Fusion, Surveillance Systems
Abstract: Within an intelligent building, it is expected to offer various intelligent services by recognizing residents along with their lifestyle and needs. One of the key issues for realizing the intelligent building is how to detect the locations of residents, so that it can provide the interactive services based on the identified need and requests. In this work, we develop a wireless pyroelectric sensory system embedded with traditional fire detector, which can be implanted on the ceiling. Both of wireless transmission model and pyroelectric sensor monitoring system can provide the rough information of residents’ location respectively. These data can be further improved by reducing the sensory uncertainty through covariance intersection (CI) data fusion method. Wireless pyroelectric sensor system also works on multi target tracking which suffers by pyroelectric localization system. With the location obtained from wireless pyroelectric sensor system, intelligent building can offer suitable services.

Keywords: Navigation, Motion Control, Dynamics
Abstract: This paper presents feedback control laws for pursuing and catching a fly ball by taking Chapman's hypothesis into the closed-loop system connecting perceptions and actions. Through the analysis of the closed-loop system, we make it clear that the hypothetical trajectory Chapman showed is a special dynamic solution of the closed-loop system. Moreover, using a motion-analyzing technique over a finite time, it is shown that the proposed feedback control laws make it possible to generate a pursuing trajectory automatically that a fly ball can be caught in the right place and at the right time. It is also shown that the pursuing trajectory gets closer to the one Chapman showed as a feedback gain increases. In addition, we compare the proposed feedback control laws with Proportional Navigation (PN) which is the most common navigation technique for tracking a moving target, and demonstrate that the proposed control laws perform better than PN.

Keywords: Localization, Range Sensing, Mapping
Abstract: Moving objects are present in many robotic applications. An accurate detection and motion estimation of these objects can be crucial for the success and safety of the robot and people surrounding it. This paper presents a new probabilistic framework for clustering dependent or relational data, applied to the problem of motion clustering and estimation. While conventional techniques such as scan differencing perform well in many cases, they usually assume that a good pose estimate is available and fail when points belonging to dynamic objects show some overlap in consecutive readings. The technique proposed, CRF-Clustering, by explicitly reasoning about the underlying motion of the object, is able to deal with poor initial motion estimate and overlapping points. Moreover, it is able to consider the dependencies between neighbor points in the scans to reduce the noise in the clustering assignment. The model parameters can be estimated from labeled data in a statistically sound learning procedure. Experiments show that CRF-Clustering is able to detect moving objects, cluster them and estimate their motion.

Keywords: Learning and Adaptive Systems, Redundant Robots, Motion Control
Abstract: We present an adaptive control approach combining forward kinematics model learning methods with the operational space control approach. This combination endows the robot with the ability to realize hierarchically organised learned tasks in parallel, using tasks null space projectors built upon the learned models. We illustrate the proposed method on a simulated 3 degrees of freedom planar robot. This system is used as a benchmark to compare our method to an alternative approach based on learning an extended Jacobian. We show the better versatility of the retained approach with respect to the latter.

Keywords: Control Architectures and Programming, Cooperating Robots, Telerobotics
Abstract: This paper proposes two new multilateral shared control architectures for dual-user haptic training systems. Similar to the architecture previously proposed in [1], the controllers allow interaction between both users, the trainee and the trainer, as well as between the users and the virtual slave robot and environment. However, the newly proposed architectures provide increased maneuverability and enhanced sense of environment to the users. The kinesthetic performance of the proposed control architectures are analyzed under different operating conditions. Furthermore, the architectures are implemented on a dual-user haptic simulation testbed for user study experiments to investigate the effectiveness of the proposed architectures in terms of sense of environment, maneuverability, and guidance.

Keywords: Control Architectures and Programming, Learning and Adaptive Systems, Navigation
Abstract: Hybrid deliberative-reactive control architectures are a popular and effective approach to the control of robotic navigation applications. However, the design of said architectures is difficult, due to the fundamental differences in the design of the reactive and deliberative layers of the architecture. We propose a novel approach to improving system-level performance of said architectures, by improving the deliberative layer's model of the reactive layer's execution of its plans. Quantitative and qualitative results from a physics-based simulator are presented.

Keywords: Adaptive Control
Abstract: In the face of large scale parametric uncertainties, the single model (SM)-based classical adaptive control approach demands high observer, controller and adaptation gains in order to achieve good tracking performance. The well known problem of having high-gain based design is that it amplifies the input and output disturbance as well as excites hidden unmodeled dynamics causing poor tracking performance. In this paper, a multi-model based adaptive design is proposed to reduce the level of parametric uncertainty in order to reduce the observercontroller gains. The key idea of this approach is to allow the parameter estimate of the SM-based classical adaptive control design to be reset into a model that best approximates the plant among a finite set of candidate models. For this purpose, we uniformly distribute the compact set of unknown parameters into a finite number of smaller compact subsets. Then we design a family of candidate controllers for each of these smaller compact subsets. The derivative of the Lyapunov function candidate is used as a resetting criterion to identify a candidate model that closely approximates the plant at each instant of time. The proposed method is evaluated on a 2-DOF robot manipulator to demonstrate the effectiveness of the theoretical development.

Keywords: Flexible Arms, Motion Control, Dynamics
Abstract: This paper presents a discrete-time decentralized control scheme for identification and trajectory tracking of a two degrees of freedom (DOF) robot manipulator. A recurrent high order neural network (RHONN) structure is used to identify the plant model and based on this model, a discrete-time control law is derived, which combines discrete-time block control and sliding modes techniques. The neural network learning is performed online by Kalman filtering. A controller is designed for each joint, using only local angular position and velocity measurements. These simple local joint controllers allow trajectory tracking with reduced computations. The proposed scheme is implemented in real-time to control a two DOF robot manipulator.

Keywords: SLAM, Cooperating Robots, Computer Vision
Abstract: In this paper we present a new vision-based SLAM approach for multi-robot formulation. For a cooperative map reconstruction, the robots have to know each other's relative poses, but estimating these at the start of operation puts a limit on real applications. In our study, the robots start the single SLAM with their own global coordinate, and merge their maps during the operation by detecting the overlapped region of their maps. The robots automatically recognize the occurrence of map overlapping by matching their current frame with the maps built by other robots. With the robust data association technique from the ceiling-vision based SLAM, the proposed algorithm robustly detects the overlapping regions and estimates the accurate transformations for map alignment. In our experiment, we have verified that our algorithm successfully enables the multi-robot SLAM without any initial correspondence or encounter of robots.

Keywords: SLAM, Mapping, Search and Rescue Robots
Abstract: Simultaneous Localization and Mapping (SLAM) suffers from a quadratic space and time complexity per update step. Recent advancements have been made in approximating the posterior by forcing the information matrix to remain sparse as well as exact techniques for generating the posterior in the full SLAM solution to both the trajectory and the map. Current approximate techniques for maintaining an online estimate of the map for a robot to use while exploring make capacity-based decisions about when to split into sub-maps. This paper will describe an alternative partitioning strategy for online approximate real-time SLAM which makes use of normalized graph cuts to remove less information from the full map.

Keywords: SLAM, Computer Vision
Abstract: Particle Filters have been widely used as a powerful optimization tool for nonlinear, non-Gaussian dynamic models such as Simultaneous Localization and Mapping (SLAM) and visual tracking. Particle filters, however, often suffer from particle impoverishment, which is caused by a mismatch between proposal distribution and target distribution. To solve this problem, we propose a new method to improve the efficiency of particle filters by employing the Particle Swarm Optimization (PSO), which is a kind of swarm intelligence algorithm. The PSO, especially its variant for dynamic models, is combined with the generic particle filter to get samples that are well matched with target distribution. The resulting filter is applied to a vision based-SLAM system and its performance is tested. We present experimentalresults that demonstrate improved accuracy in localization and mapping at the same or less computational cost than theconventional particle filters.

Keywords: SLAM, Computer Vision, Biologically-Inspired Robots
Abstract: Simultaneous Localization and Mapping (SLAM) based on visual information is a challenging problem. One of the main problems with visual SLAM is to find good quality landmarks, that can be detected despite noise and small changes in viewpoint. Many approaches use SIFT interest points as visual landmarks. The problem with the SIFT interest-point detector, however, is that it results in a large number of points, of which many are not stable across observations. We propose the use of local symmetry to find regions of interest instead. Symmetry is a stimulus that occurs frequently in everyday environments where our robots operate in, making it useful for SLAM. Furthermore, symmetrical forms are inherently redundant, and can therefore be more robustly detected. By using regions instead of points-of-interest, the landmarks are more stable. To test the performance of our model, we recorded a SLAM database with a mobile robot, and annotated the database by manually adding ground-truth positions. The results show that symmetrical regions-of-interest are less susceptible to noise, are more stable, and above all, result in better SLAM performance.

Keywords: Localization, SLAM
Abstract: In this paper, we propose an algorithmic compass that yields the heading information of a mobile robot using the vanishing point in indoor environments: VPass. With the VPass, a loop-closing effect (which is a significant reduction of errors by revisiting a known place through a loop) can be achieved even for a loop-less environment. From the implementation point of view, the VPass is useful because it can be appended upon any existing navigation algorithms. Experimental results show that the VPass yields accurate angle information in indoor environments for paths with lengths of around 200m.

Keywords: Range Sensing, Computer Vision
Abstract: This paper presents a method of light pattern blur estimation for its application to automatic projector focus control in structured light 3D camera. To overcome shortcoming of the conventional methods for estimating blur of light pattern, we propose to normalise the light pattern image incorporating reference images. Which are made available by a structured light 3D camera. The reference black and white patterns are utilised in such a way as to eliminate the dependence of intensity variation around an edge on surface reflectivity. Then the unknown blur radius is estimated from the first derivative of normalised edge. Experimental results on both synthetic and real images verify that the proposed method is indeed independent of surface reflectivity and is accurate and sensitive enough to the small change of blur. Finally, based on the proposed light pattern blur estimation, a structured light 3D camera that is equipped with automatic multi-stage focus control in a beam projector has been built to demonstrate its capability of capturing the 3D workspace of large depth variations.

Keywords: Field Robots, Manipulation Planning
Abstract: This paper presents the investigation on mobile manipulation of a self-reconfigurable tracked mobile robot, using its tracks for both manipulation and locomotion. It is desirable for a mobile robot to possess manipulation capability in unstructured environments, especially in the scenario which is unsuitable for human beings. However, it is not convenient for such a mobile robot to carry an onboard manipulator and perform grasping and placing operations. An alternative is to realize the manipulation potential of the existing parts and perform manipulation without attaching additional hardware. Besides the enhanced locomotion ability, a self-reconfigurable tracked mobile robot has great potential in manipulation, which may take the forms of box-pushing, cylinder-moving or lateral hitting. However, the manipulation with tracks has to be controlled properly. One challenge is to optimize the tracks’ configuration so as to get the optimal contact point. Furthermore, the speed and acceleration of the mobile robot have dramatic influence on mobile manipulation with tracks. To verify the effectiveness of the proposed algorithms, experiments are conducted using a tracked mobile robot in our laboratory.

Keywords: Dexterous Manipulation, Motion Control
Abstract: In this paper, we study the problem of door-opening by using modular re-configurable robot (MRR). With respect to the multi-mode feature of the joint modules of MRRs, we firstly propose an online mode-switch strategy for all joint modules so that each joint module can be easily and straightforwardly determined when should be switched from the passive working mode to the active working mode during door-opening process. Based on the proposed mode-switch strategy, a hybrid control scheme is proposed to solve the problem of door-opening. In the hybrid control scheme, different control approaches are used for the motion control of joint modules in different working modes. For the passive joint modules, a feed forward torque control approach is used to compensate the joint friction to ensure them move freely; for the active joint modules, a decomposition-based control and a feedback position control approach is used for the joints working at the defined current-active and post-active mode, respectively. The control laws used for the active joints are theoretically proved to guarantee the asymptotic convergence of the position errors of the active joints and that of the door, in the proposed hybrid control scheme. Simulation results used to demonstrate the validity and efficiency of the proposed modes-witch strategy and the hybrid control scheme.

Keywords: Manipulation Planning, Motion Control, Path Planning for Manipulators
Abstract: Shape control of a deformable object by a robotic system is a challenging problem because of the difficulty of imposing shape change by a finite number actuation points to an essentially infinite dimensional object. In this paper, a new approach to shape changing of deformable objects by a system of manipulators is presented. First, an integrated dynamic equation of motion for a system of multiple manipulators handling a deformable object is developed. The initial and the final shapes of the deformable object are specified by curves that represent the boundary of the object. We design an optimization-based planner that minimizes an energy-like criterion to determine the locations of the contact points on the desired curve representing the final shape of the object. The motion of each manipulator is controlled independently without any communication between them. The simulation results demonstrate the efficacy of the proposed method.

Keywords: Medical Robots and Systems, Force and Tactile Sensing
Abstract: Minimally Invasive Surgery (MIS) and robot surgery have opened new ways to perform surgical operations in a safer and simultaneously faster manner. In an effort to follow this minimally invasive trend, this paper presents the feasibility study of a novel fibre-optic catheter prototype. This prototype sensor has the ability to measure forces from the sides and tip. Classification of forces from multiple positions on a catheter provides valuable information for safe navigation inside the vasculature and heart of a patient. This sensor employs two fibre-optic schemes, one for the tip and one for the sides of the catheter; it is made entirely of plastic, making it compatible with Magnetic Resonance Imaging (MRI). A test bench was used to determine the linearity coefficients during static load-ing. These initial experiments on the prototype gave rise to an ideal linear force response coupled with low hysteresis. Finally, an experiment which tries to simulate the human blood vessel achieved satisfying results during dynamic sensor movement.

Keywords: Motion Control, Dynamics
Abstract: Mechanical backlash is a common trouble in all servo mechanisms that is created by mechanical defects i.e. wear or looseness. Backlash imposes nonlinearity on a linear control system and may be contributed to a limit cycle. Considering mechanical subsystem of a servo axis as an elastic two-mass system, modeling the backlash with a dead zone and choosing reduced order control system for the speed and current controller, the frequency bandwidth of vibration is estimated. The estimated frequency is supported by the experimental vibration analysis of six different machine tools. To eliminate unwanted vibration, a backlash detection and suppression approach is proposed in this paper. In the case of vibration, load sensor is disregarded and the regulator conducts the setting speed of interpolator to the drive. Then stability is satisfied with the cost of some tracking error. When stability is detected load sensor is considered and the regulator output converges to the speed provided by the position control. To examine the approach, dynamic model of a real servo axis is obtained and it is validated by experimental data. Then the proposed modified control system is simulated. Keywords—Backlash, machine tools, Vibration, Regulator.

Keywords: Nonholonomic Motion Planning, Evolutionary Robotics
Abstract: This paper presents a novel evolutionary G3 –continuous (continuous-differentiable curvature) path planner for nonholonomic wheeled mobile robots. The evolutionary path planner generates intermediate configurations connected via η3-splines that yields a collision-free G3 –continuous path, where each point on the path has a closed-form expression. The path planner is implemented as an architecture of island parallel ge-netic algorithm (IPGA) running a variable-length genetic algo-rithm in each island. The techniques of spatial fitness-sharing in search space and a crowded measure of generated paths are inte-grated in the planner to implement a high-diversity evolutionary optimizer of paths that could self-adjust the spacing and number of intermediate configurations. The experimental result demon-strates the robustness and self-adjusting capability of evolutionary path planner in discovering shorter and smoother composite η3-splines paths in complex environments.

Keywords: Entertainment Robotics, Social Human-Robot Interaction, AI Reasoning Methods
Abstract: In this article, the system of a Chinese chess robot is demonstrated, and it presents the latest development of artificial intelligence. The robot could play Chinese chess autonomously with human, it has “eyes” that can recognize the pieces on the chessboard and move them with its mechanical arm. Furthermore, it has a higher intelligence which could approach the “master” level. The paper will be organized as follows: First, the general structure and seven subsystems will be introduced briefly. Then some key techniques used in Chinese chess gaming system will be discussed.

Keywords: Navigation, Intelligent Vehicles
Abstract: This paper presents a new path planning algorithm that uses adaptive random walks to incrementally construct a roadmap in the robot’s free configuration space. This algorithm, named Incremental Adaptive Random Walks (iARW), uses a modified version of the ARW algorithm proposed by Carpin and Pillonetto [1] for exploring the configuration space and storing the discovered path in a roadmap. Thus, the main idea is to use bidirectional adaptive random walks to explore the configuration space but also to use and expand the roadmap whenever possible. With this approach it is possible to construct a roadmap that captures the connectivity of the free configuration space without a preprocessing phase. A comparison of our approach with other state of the art path planners illustrates the good performance of the proposed method.

Keywords: Range Sensing, Recognition, Field Robots
Abstract: This paper describes a LIDAR-based perception system for ground robot mobility, consisting of 3D object detection, classification and tracking. The presented system was demonstrated on-board our autonomous ground vehicle MuCAR-3, enabling it to safely navigate in urban traffic-like scenarios as well as in off-road convoy scenarios. The efficiency of our approach stems from the unique combination of 2D and 3D data processing techniques. Whereas fast segmentation of point clouds into objects is done in a 2 12 D occupancy grid, classifying the objects is done on raw 3D point clouds. For fast object feature extraction, we advocate the use of statistics of local point cloud properties, captured by histograms over point features. In contrast to most existing work on 3D point cloud classification, where real-time operation is often impossible, this combination allows our system to perform in real-time at 0.1s frame-rate.

Keywords: Visual Tracking, Surveillance Systems, Field Robots
Abstract: We propose a BEST (Background subtraction and Enhanced camShift Tracking) method for a scout robot tracking a moving object in real time. A modified back subtraction method based on time axis is used to segment the moving object in a complicated environment. The centroid and area are chosen as the feature to judge target. We proposed a novel method that combines Camshift, AWS (Adaptive Window Selecting method) and Kalman predicting algorithm together to track the detected object. Experiments based on a DSP image processing system in a scout robot indicate the feasibility and robustness of our method.

Keywords: Education Robotics, Autonomous Agents, Domestic Robots
Abstract: LabRat(TM) is an autonomous, self-contained mobile robot kit with batteries, motors, two bumper whisker sensors, and three infrared proximity sensors that double as channels for "Rat-to-Rat" communication. The vehicle determines its position with an optical sensor that detects movement in both lateral directions. The LabRat(TM) design is completely open source, including software examples and libraries. LabRat(TM) is designed to fit inside the body of a computer mouse and has applications in the classroom, the lab and the home. The device has been successfully used in an undergraduate robotics class.

Keywords: Computer Vision, Recognition, Learning and Adaptive Systems
Abstract: There is a subset of objects for which interaction can provide numerous cues to those objects' identity. Robots are often in situations where they can take advantage being able to observe humans interacting with the objects. In this paper, we define this subset of `interactionable' objects for which we use our Multiple-Cue Object Recognition algorithm (MCOR) to take advantage of using multiple cues. We present two main contributions: 1) the introduction of cue-driven equivalence class discrimination, and 2) the integration of this technique, the general MCOR algorithm, and a hierarchical activity recognition algorithm also presented in this paper, demonstrated on data taken from a static Sony QRIO robot observing a human interacting with objects. The hierarchical activity recognition provides an important cue for the object recognition.

Keywords: Biologically-Inspired Robots, Biomimetics, Marine Robotics
Abstract: This paper describes the design of a biomimetic inspired fish swimming like UUV based on 2-D ocillating foil machanism which plays guiding role in biomimetic propulsion research field, the relation between vorticity control and motion control parameters for 2-D ocillating foil has been built, a fuzzy logic vorticity controller is designed to achieve straight line maneuverable swimming and thrust efficiency can be ensured at the same time. Experimental result of field test shows that an obiviously improved vehicle performance is obtained. Meanwhile, burst-and-coast manevering is found to be a more effective swimming mode for the vihicle while compared with steady swimming.

Keywords: Haptics and Haptic Interfaces, Rehabilitation Robotics, Virtual Reality and Interfaces
Abstract: In this paper, we propose a novel task-oriented motor function training and assistance of upper limbs system after brain injured such as stroke based on Virtual-Reality. In this system, two kinds of training approaches are developed. One is tracking training with path-unlimited based on a mass-spring-damper force model, and the other is tracking training with path-limited based on a compound force model. Both of training approaches are same that coordination motion of two hands is needed. We want to re-examine how effective the haptic sensory and visual sensory are in training of upper limbs. Further, we enhance the effect of system through adding assistance in order to help mild stroke patients to recovery. This system is convenient and compact so that it is suitable for home-based rehabilitation.

Keywords: Behaviour-Based Systems, Calibration and Identification, Gesture, Posture, Social Spaces and Facial Expressions
Abstract: In this work a multimodal head-mounted device for the assessment of social orienting behaviour in children between 12 and 24 months is presented. The device is specifically designed to be used in poorly structured and uncontrolled environments such as day-care centres. Accordingly, a calibration procedure is described which fully exploits the multimodal approach and which is particularly suitable for an ecological assessment.

Keywords: Legged Robots, Kinematics
Abstract: In this paper, the kinematic model of a quadruped robot is derived. The model is equivalent to that of a parallel manipulator, in that each leg can be seen as a manipulator. However, the model is extended to consider that in one gait cycle some legs are in contact with the ground and others are not. In order to obtain the inverse kinematics model, this paper presents as contribution the use of the extended Kalman filter as optimizer in two different situations of the leg motion: unconstrained case, for the swing leg(s), and constrained case, for the leg(s) in contact with the ground. This method was evaluated for locomotion in plain and inclined surfaces. The results obtained with the kinematics model were satisfactory when implemented in a point-to-point trajectory in simulation, and also in an experiment with a four-legged platform with three degrees of freedom in each leg.

Keywords: Biologically-Inspired Robots
Abstract: Living organisms have various kinds of flexibility and robustness which are realized by ``yuragi,'' or biological fluctuations or noises. The bacterial motion is one of the noise-based motion, since they can move towards the higher concentration of some chemical which they prefer although they have only a limited 1-DOF of flagella for mobility. Bacteria also have only a limited sensory device which cannot detect the spatial gradient of the chemical at a time. The simple strategies that bacteria take to realize chemotaxis are (1) to tumble (or turn) to change its orientation randomly with unbundled flagella in various directions being hit by surrounding water molecules, and (2) to change the frequency of tumbling according as the time change of chemical concentration. In this paper, we describe a quite small and simple, 1-DOF swimming robot developed by mimicking the bacterial motion generation mechanism. The robot only has a single motor and a single sensor (a photo detector), however by changing the orientation due to various noises which exist in the environment, and by changing the frequency of turning, the robot can approach the goal. Experimental results indicates that the robot statistically approaches the goal (light source) in two dimensional space with 1-DOF actuator, which is impossible for the robot to achieve without the utilization of the noises in the environment.

Keywords: Path Planning for Multiple Mobile Robot Systems, Networked Robots
Abstract: Utilizing multiple paths between network hosts (such as robots or sensors) will improve network performance, path availability and connection reliability. This paper presents a cross layer multiple path approach named Proxy Server based Multipath Connection. Multiple paths are set up via a set of intermediate proxy servers using IP tunneling. Packet distribution and reassembly are achieved by inserting a thin layer between the network layer and the transport layer. On the sender side, packets are distributed across multiple paths based on predefined striping schemes. On the receiver side, a double buffer approach is proposed to solve the TCP sequence number persistent reordering problem. A prototype was implemented on the Linux and Windows systems. Experimental results show that the proposed approach can improve network throughput and is robust to network congestion and link breakage.

Keywords: Medical Robots and Systems
Abstract: Entry position of the graft is very important in anterior cruciate ligament (ACL) reconstruction. However the determination of entry position is very difficult to the surgeon. In this paper, a navigation and evaluation system assisted by the 6 DOF robot is implemented for the simulation evaluation and planning insertion points based on quadrant method for the femur and Stäublis method for the tibia on the lateral X-ray image of knee joint. Meanwhile, the implementation of the key technologies such as image correction, image registration, C-arm calibration, video tracking, bone surface reconstruction, image fusion, 6-DOFS robot, and virtual simulation are introduced. Finally, Experiments about the tunnel planning method and real time tracking of surgical apparatus are implemented on 8 bone of plastic models (Sawbone, Swiss) and 10 bones of the goat. In the experiment, the tibia rotates around the femur under the surgeon’s implementation to evaluate the planning result with the virtual simulation and evaluation module. The positioning error is 1.59mm from analysis on 30 space targets. The virtual reconstruction ACL is satisfied with two important criteria of the best isometry and collision detection between graft and intercondylar surface of femur. The results are well accepted in operations. In order to satisfying with the request of exact operation in ACL reconstruction, we have developed 6-DOFS passive robot to assist the surgeons entry positioning and drilling of implant tunnels, implementing exact operation in knee joint.

Keywords: Programming Environment, Legged Robots, Entertainment Robotics
Abstract: To facilitate the development of intelligent robot, a virtual entity based rapid prototype developing framework (VE-RPDF) is proposed. It aims at helping design intelligent robot through the following steps: rapidly setting up a robot prototype, coding for the control strategy and algorithm, and optimizing the robot design by testing it on both virtual entity and real robot. With VE-RPDF, two types of robots, including wheeled robot and humanoid robot, are developed, and one of them is introduced as a case to verify the validation of VE-RPDF.

Keywords: Networked Robots, Mapping, Sensor Networks
Abstract:

Keywords: Humanoid Robots, Legged Robots
Abstract: In this paper, we generate a biped gait of a humanoid robot that looks like a human's one. To generate a human like motion, we first capture the walking motion of a human. Then, we analyze the captured data and obtain several information such as the relationship between the step length and waist height etc. We consider applying these informations to the real humanoid robot. Also, when the human walks, the sway of the waist is smaller than most of the humanoid robot's one. By compensating the angular momentum of the robot and by modifying the ZMP trajectory, we show that sway of the robot's waist can be smaller. We show the effectiveness of the proposed method through simulation and experimental results.

Keywords: Humanoid Robots
Abstract: This paper proposes a new walking pattern generation method for humanoid robots. The proposed method consists of feedforward control and feedback control for walking pattern generation. The pole placement method as a feedback controller changes the poles of system in order to generate more stable and smoother walking pattern. The advanced pole-zero cancelation by series approximation(PZCSA) as a feedforward controller plays a role of reducing the inherent property of linear inverted pendulum model (LIPM), that is, non-minimum phase property due to an unstable zero of LIPM and tracking efficiently the desired zero moment point (ZMP). The efficiency of the proposed method is verified by three simulations such as arbitrary walking step length, arbitrary walking phase time and sudden change of walking path.

Keywords: Humanoid Robots, Legged Robots, Motion Control
Abstract: Generating stable dynamic motions for a biped robot in real time is difficult due to the unstable nature of biped systems and their high degrees of freedom. We propose an approximate dynamics model for biped robots with three masses and no kinematic constraints. We also propose a relaxed boundary condition called “the divergent component of motion”. These techniques allow us to generate walking gait patterns with large margin from the edges of support polygon in real time.

Keywords: Humanoid Robots, Legged Robots, Motion Control
Abstract: Bipedal running can easily result in a fall due to poor availability of the ground reaction force at the boundary of the flight and support phases. We propose methods to decompose and synthesize a running gait pattern into vertical, horizontal and rotational components so that time-dependent ground friction limits are satisfied. We also extend previously proposed boundary condition, the divergent component of motion, for switching walking gait patterns into running which involves vertical acceleration of the center of gravity. Using these techniques, running at 10 km/h is achieved on a real robot whose dimension are same as ASIMO.

Keywords: Humanoid Robots
Abstract: This paper is presenting a method to generate real-time running and jumping trajectories that can be applied to bipedal humanoid robots. The proposed method is based on maintaining the overall dynamic balance by using the ZMP stability criterion throughout support phases. To be able to reach this goal, we utilize ZMP equations in spherical coordinates, so that the rate change of angular momentum terms in ZMP equations are included naturally by using Eulerian equations of motion for unsymmetrical bodies. Thus, undesired torso angle fluctuation is expected to be more restrainable comparing to other methods in which angular momentum information is ignored or zero-referenced. Applying the aforementioned technique, we primarily simulated running motion on a dynamic 3-D simulator. Secondarily, one-legged jumping experiments were conducted on the actual bipedal robot. In conclusion, we obtained repetitive and successful running and jumping cycles which satisfactorily verify the proposed method.

Keywords: Rehabilitation Robotics, Underactuated Robots
Abstract: This paper introduces a novel exoskeleton device (HANDEXOS) for the rehabilitation of the hand for post-stroke patients. The nature of the impaired hand can be summarized in a limited extension, abduction and adduction leaving the fingers in a flexed position, so the exoskeleton goal is to train a complete opening movement from a strongly contracted and closed position of the impaired hand. The mechanical design, of HANDEXOS offers the possibility to overcome the exoskeleton limits often related to the general high level of complexity of the structure, mechanism and actuation. We describe the mechanical design of the index finger module, the dynamic model and some preliminary experimental results.

Keywords: Rehabilitation Robotics
Abstract: This paper presents a new application in the field of rehabilitation robotics. It is part of a research project which consists of the development of a robotic leg prosthesis for above knee amputees. This application aims at providing real-time estimates of the prosthesis foot orientation with respect to ground. An Extended Kalman Filter (EKF) is used in order to estimate the foot orientation based on gyroscope and infrared measurements. Moreover a constraint equation is also included in the EKF to guarantee the constraints in the estimates. Preliminary tests were performed in a platform built for the prosthesis prototype. The results discussed in this paper reveal the feasibility of such technique.

Keywords: Rehabilitation Robotics, Physical Human-Robot Interaction, Navigation
Abstract: In order to allow severely disabled people who cannot move their arms and legs to steer an automated wheelchair, this work proposes the combination of a non-invasive EEG-based human-robot interface and an autonomous navigation system that safely executes the issued commands. The robust classification of steady-state visual evoked potentials in brain activity allows for the seamless projection of qualitative directional navigation commands onto a frequently updated route graph representation of the environment. The deduced metrical target locations are navigated to by the application of an extended version of the well-established Nearness Diagram Navigation method. The applicability of the system proposed is demonstrated by a real-world pilot study in which nine untrained subjects successfully navigated an automated wheelchair, requiring only some ten minutes of preparation.

Keywords: Rehabilitation Robotics, Medical Robots and Systems, Control Architectures and Programming
Abstract: This paper proposes a seven degrees of freedom (7DOF) upper-limb motion assist exoskeleton robot (SUEFUL-7) and its electromyography (EMG) signal based control method for assisting the motions of shoulder vertical and horizontal flexion/extension, shoulder internal/external rotation, elbow flexion/extension, forearm supination/ pronation, wrist flexion/extension, and wrist radial/ulnar deviation of physically weak individuals. In the proposed control method, impedance controller is applied to the muscle-model-oriented control method by considering the end effecter force vector. Experiments have been performed to evaluate the effectiveness of the proposed robot system.

Keywords: Social Human-Robot Interaction, Underactuated Robots, Learning and Adaptive Systems
Abstract: In this paper, adaptive dynamic coupling control is considered for hybrid joint, which could be switched to either active (actuated) or passive (under-actuated) mode, for human-symbiotic wheeled mobile manipulators, in the presence of parametric and functional uncertainties. The constraints of the system consist of kinematic constraints and dynamic constraints. Based on Lyapunov synthesis, adaptive coupling control using physical properties of wheeled mobile manipulators proposed for passive hybrid joints ensures that the system outputs track the given bounded reference signals within a small neighborhood of zero, and guarantees semi-global uniform boundedness of all closed loop signals. The effectiveness of the proposed controls is verified through extensive simulations.

Keywords: Mapping, Search and Rescue Robots, Service Robots
Abstract: This paper presents a feature based 3D mapping approach with regard to obtaining compact models of semistructured environments such as partially destroyed buildings where mobile robots are to carry out rescue activities. To gather the 3D data, we use a laser scanner, employing a nodding data acquisition system mounted on both real and simulated robots. Our segmentation algorithm comes up from the integration of computer vision techniques, allowing for a fast separation of points corresponding to different, not necessarily planar, surfaces. The subsequent extraction of geometrical features out of each region’s points is done by means of least-squares fitting. A Maximum Incremental Probability algorithm formulated upon the Extended Kalman Filter provides 6D localization and produces a map of planar patches with a convex-hull based representation. Scenarios from the Unified System for Automation and Robot Simulation (USARSim), including world models from past RoboCup Rescue editions’ arenas, have been utilized to conduct some of our experiments.

Keywords: Computer Vision, Localization, Mapping
Abstract: During Simultaneous Localization And Mapping, geometrical constraints are established between map features. These constraints, introduced through measurements and mo- tion prediction, produce a bending effect in the event of closing a large loop. In this paper we present a discussion of the bending problem for trajectory based representations. Furthermore, we propose a generic approach that exploits common geometrical

constraints in human-made environments through the use of a

Heading Based Curvature measurement to reduce the bending effect. We show by means of experimental results that our approach increases significantly both the global and local map accuracy. these error models are simplified by estimating a single covariance from test data which is then used through the complete estimation. This simplification introduces artifacts in the event of closing a large loop. For delayed state approaches, this is known as the trajectory bending behavior. At every step in a ESDSF new links are introduced between the current pose and the previous poses through both control of the actuation, and measurements. Assuming that the number of measurements remains constant [10] and no loops

Keywords: Mapping, Localization, Range Sensing
Abstract: This article addresses fast 3D mapping by a mobile robot in a predominantly planar environment. It is based on a novel pose registration algorithm based entirely on matching features composed of plane-segments extracted from point-clouds sampled from a 3D sensor. The approach has advantages in terms of robustness, speed and storage as compared to the voxel based approaches. Unlike previous approaches, the uncertainty in plane parameters is utilized to compute the uncertainty in the pose computed by scan-registration. The algorithm is illustrated by creating a full 3D model of a multi-level robot testing arena.

Keywords: Mapping, Computer Vision
Abstract: The typical SLAM mapping system assumes a static environment and constructs a map that is then used without regard for ongoing changes. Most SLAM systems, such as FastSLAM, also require a single connected run to create a map. In this paper we present a system of visual mapping, using only input from a stereo camera, that continually updates an optimized metric map in large indoor spaces with movable objects: people, furniture, partitions, etc. The system can be stopped and restarted at arbitrary disconnected points, is robust to occlusion and localization failures, and efficiently maintains alternative views of a dynamic environment. It operates completely online at a 30 Hz frame rate.

Keywords: Mapping, Localization, SLAM
Abstract: This paper presents a method of 3D mapping using a binocular stereo camera with automatic recovery from registration failure. We employ edge points as map element, and apply a variant of ICP algorithm to the inter-frame registration. The method detects failure in the registration due to erratic camera motion or moving objects and recovers from the failure by searching a good image to resume the registration using edge-point SIFT descriptors. In experiments, our method successfully built detailed 3D maps robustly in indoor and outdoor environments under various conditions.

Keywords: Field Robots, Sensor Fusion, Range Sensing
Abstract: This work aims to promote reliability and integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicle (UGV) autonomy. For this purpose, a comprehensive UGV system, comprising many different exteroceptive and proprioceptive sensors has been built. The first contribution of this work is a large, accurately calibrated and synchronised, multi-modal data-set, gathered in controlled environmental conditions, including the presence of dust, smoke and rain. The data have then been used to analyse the effects of such challenging conditions on perception and to identify common perceptual failures. The second contribution is a presentation of methods for mitigating these failures to promote perceptual integrity in adverse environmental conditions.

Keywords: Field Robots, Search and Rescue Robots, Service Robots
Abstract: The ability of mobile robots to quickly and accurately analyze their dynamics is critical to their safety and efficient operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this must be considered in an analysis of robot motion. Here a Multi-Element generalized Polynomial Chaos (MEgPC) approach is presented that explicitly considers vehicle parameter uncertainty for long term estimation of robot dynamics. It is shown to be an improvement over the generalized Askey polynomial chaos framework as well as the standard Monte Carlo scheme, and can be used for efficient, accurate prediction of robot dynamics.

Keywords: Field Robots, Search and Rescue Robots, Service Robots
Abstract: The ability of mobile robots to generate feasible trajectories online is an important requirement for their autonomous operation in unstructured environments. Many path generation techniques focus on generation of time- or distance-optimal paths while obeying dynamic constraints, and often assume precise knowledge of robot and/or environmental (i.e. terrain) properties. In uneven terrain, it is essential that the robot mobility over the terrain be explicitly considered in the planning process. Further, since significant uncertainty is often associated with robot and/or terrain parameter knowledge, this should also be accounted for in a path generation algorithm. Here, extensions to the rapidly exploring random tree (RRT) algorithm are presented that explicitly consider robot mobility and robot parameter uncertainty based on the stochastic response surface method (SRSM). Simulation results suggest that the proposed approach can be used for generating safe paths on uncertain, uneven terrain.

Keywords: Field Robots
Abstract: In the area of autonomous multi-robot cooperation, much emphasis has been placed on how to coordinate individual robot behaviors in order to achieve an optimal solution to task completion as a team. This paper presents an approach to cooperative multi-robot reinforcement learning based on a hybrid state space representation of the environment to achieve both task learning and heterogeneous role emergence in a unified framework. The methodology also involves learning space reduction through a neural perception module and a progressive rescheduling algorithm that interleaves online execution and relearning to adapt to environmental uncertainties and enhance performance. The approach aims to reduce combinatorial complexity inherent in role-task optimization, and achieves a satisficing solution to complex team-based tasks, rather than the global optimal solution. Empirical evaluations are conducted in simplified foraging tasks for this proposed framework and simulation results are presented to show the performance enhancement that can be generalized for other multi-robot collaboration systems.

Keywords: Field Robots, Motion Control, Robotics in Agriculture and Forestry
Abstract: Accurate control of high-speed mobile robots moving off-road constitutes a challenging robotic issue: numerous time-varying dynamic phenomena (and first of all, sliding effects) are no longer negligible and must explicitly be taken into account in control design, in order to ensure high accuracy path tracking. Since these phenomena are hardly measurable at a reasonable cost, they have to be estimated on-line. A backstepping observer is here proposed, in order to supply on-line tire cornering stiffnesses (i.e. grip conditions) as well as mobile robot sideslip angles. It takes part of the complementarity between kinematic and dynamic mobile robot models, in order to significantly decrease the number of required robot inertial parameters (since their values are sometimes difficult to obtain). Full scale experiments demonstrate that the proposed observer can supply reactive and reliable sideslip angle estimates, so that high accuracy path tracking can still be achieved , whatever grip conditions and vehicle velocity.

Keywords: Navigation, Localization, Field Robots
Abstract: This paper presents two new approaches that enable the use of linear landmarks for planning paths with uncertainty in position in outdoor environments. The first approach uses a combination of forward simulation and entropy to reduce the dimensionality of the search space, while still preserving most of the information required to propagate a full covariance matrix. The second approach adds incremental binning to improve the quality of the solution while still keeping the dimensionality of the search space relatively low. These approaches provide a better compromise of speed and quality of the solution than most existing approaches, and are able to successfully utilize linear landmarks in large outdoor environments.

Keywords: Localization, Intelligent Vehicles
Abstract: Localization is a part of many automotive applications where safety is of crucial importance. We think that the best way to guarantee the safety in these applications is to guarantee the results of their embedded localization algorithms. Unfortunately localization of vehicles is mostly solved by Bayesian methods which (due to their structure) can only guarantee their results in a probabilistic way. Interval analysis allows an alternative approach with bounded-error state estimation. Such an approach provides a bounded set of configurations that is guaranteed to surround the actual vehicle configuration. We have validated the bounded-error state estimation with an outdoor vehicle equipped with odometers, a GPS receiver and a gyro. With the experimental results we compare the bounded-error state estimation with the particle filter localization in terms of consistency and computation time.

Keywords: Field Robots, Mapping
Abstract: This paper addresses the problem of vegetation detection from laser measurements. The ability to detect vegetation is important for robots operating outdoors, since it enables a robot to navigate more efficiently and safely in such environments. In this paper, we propose a novel approach for detecting low, grass-like vegetation using laser remission values. In our algorithm, the laser remission is modeled as a function of distance, incidence angle, and material. We classify surface terrain based on 3D scans of the surroundings of the robot. The model is learned in a self-supervised way using vibration-based terrain classification. In all real world experiments we carried out, our approach yields a classification accuracy of over 99%. We furthermore illustrate how the learned classifier can improve the autonomous navigation capabilities of mobile robots.

Keywords: Localization, Sensor Fusion, Intelligent Vehicles
Abstract: This paper presents the problematic of outdoor vehicle localization under the IMM (Interacting Multiple Model) approach. The IMM is now a well known modular approach, which is based on the discretization of the vehicle evolution space into simple maneuvers, represented each by a simple dynamic model such as constant velocity or constant turning etc. This allows the method to be optimized for highly dynamic vehicles. Unfortunately classical IMM shows some drawbacks concerning some real time multi sensors applications. In this work, we focus on outdoor vehicle localization with asynchronous sensors in order to report these drawbacks and then propose a new solution. Many tests carried out with simulated and real data confirm the interest for using such a solution in our applications.

Keywords: Navigation
Abstract: We propose a view-based indoor/outdoor navigation method as an extension of the view-sequence navigation. The original view-sequence navigation method uses the template matching method with normalized correlation for localization. Because the matching method is sensitive to local illumination changes, it is only used for indoor environment. In this paper, we propose to adopt the accumulated block matching method to improve robustness against locally changing illumination, in which a template is split into small patches and matched by maximizing average of the normalized correlations of all the patches. We also propose a localization criterion which helps the robot decide its motion. Our experimental results demonstrate that the proposed methods can be applied to both indoor and outdoor environments.

Keywords: Haptics and Haptic Interfaces, Rehabilitation Robotics, Human Performance Augmentation
Abstract: This paper proposes a novel wearable interface for the foot: an on-shoe tactile display that enables users to obtain information through the sense of touch of their feet. A 16-point array of actuators stimulates the sole of the foot by inducing different vibration frequencies. Experiments to study how people understand information through their feet were conducted with 20 voluntary subjects. Results show that some shapes and patterns are discriminable and that tactile-foot stimulation could be used for a wide number of applications in human-machine interaction. In particular, results show that it is possible to exploit podotactile information for navigation in space.