Keywords: Dynamics, Field Robots, Localization
Abstract: This article compares several parameterizations and motion models for improving the estimation of the nonlinear uncertainty distribution produced by robot motion. In previous work, we have shown that the use of a modified polar parameterization provides a way to represent nonlinear measurements distributions in the Cartesian space as linear distributions in polar space. Following the same reasoning, we present a motion model extension that utilizes the same polar parameterization to achieve improved modeling of mobile robot motion in between measurements, gaining robustness with no additional overhead. We present both simulated and experimental results to validate the effectiveness of our approach.

Keywords: Domestic Robots, Parallel Robots, Adaptive Control
Abstract: To solve the level-adjusting and force-tuning problems of high accurate and costly payloads when loading and unloading, a cable-driven auto-leveling parallel robot is developed. A hierarchical fuzzy controller, which has the ability to deal with the rule explosion problem, is proposed in this paper. After a brief introduction of the architecture of the closed-loop control system for the cable-driven auto-leveling parallel robot, the construction of the hierarchical fuzzy controller is set up, in which the force offsets of the four cables and the angle deviations of the two diagonal inclinations are chosen as input variables, and the output variables are the force offsets of the four linear motion units’ positions. The hierarchical fuzzy controller contains two layers – the low level layer which is used for leveling adjustment and force tuning, and the high level layer which is used to coordinate the two outputs from the low level layer. Experimental results have demonstrated that the hierarchical fuzzy controller can achieve the control objectives with high regulation accuracy and short adjusting time, and can be easily applied to the practical system.

Keywords: Control Architectures and Programming, Programming Environment
Abstract: The application of industrial robots is strongly limited by the use of old-style robot programming languages. Due to these languages, the development of robotic software is a complex and expensive task requiring technical expertise and time. Hence, the use of industrial robots is often not a question of technical feasibility but of economic efficiency. This paper introduces a new architectural approach making available modern concepts of software engineering for industrial robots. The core idea is to hide the real-time critical robot control from application developers. Instead, common functionality is provided by a generic and extensible application programming interface and can be used easily. Hence, this approach can lead to an industrialization of software development for industrial robotics.

Keywords: Adaptive Control, Parallel Robots, Motion Control
Abstract: This paper deals with nonlinear dual mode adaptive control of a redundant manipulator for a pick-and-place scenario with high acceleration (20G). For performance comparisons, a conventional Proportional-Derivative (PD) controller has also been implemented. In this context, the experimental testbed is not equipped with velocity sensors. Therefore, a high-gain observer has been implemented to estimate the articular velocities. Real-time experiments show the performance improvements obtained by the proposed control approach in comparison to the conventional one.

Keywords: Biologically-Inspired Robots, Marine Robotics, Biomimetics
Abstract: TExperimental analyses of propulsion in freely-swimming fishes have led to the development of self-propelling pectoral and caudal fin robotic devices. These biorobotic models have been used in conjunction with biological and numerical studies to investigate the effects of the fin’s kinematic patterns and structural properties on forces and flows. Data from both biorobotic fins will be presented and discussed in terms of the utility of using robotic models for understanding fish locomotor dynamics. It was shown, through the use of the robotic fins, that subtle changes to the kinematics and/or the mechanical properties of the fin can impact significantly the magnitude, direction, and time course of the fin’s 3d forces.

Keywords: Biologically-Inspired Robots, Dynamics, Marine Robotics
Abstract: Soft actuation materials, such as Ionic Polymer-Metal Composites (IPMCs), are gaining increasing interest in robotic applications since they lead to compact and biomimetic designs. In this paper, we propose the use of soft actuation materials as active joints for propelling biomimetic robotic fish. An analytical model is developed to compute the thrust force generated by a two-link tail and the resulting moments in the active joints. The computed joint moments can be combined with internal dynamics of actuation materials to provide realistic kinematic constraints for the joints. Computational fluid dynamics (CFD) modeling is also adopted to examine the flow field, the produced thrust, and the bending moments in joints for the two-link tail. Good agreement is achieved between the analytical modeling and the CFD modeling, which points to a promising two-tier framework for the understanding and optimization of robotic fish with a multi-link tail. We also show that, comparing to a one-link bending tail, a two-link tail is able to produce much higher thrust and more versatile maneuvers, such as backward swimming.

Keywords: Biomimetics, Biologically-Inspired Robots, Mechanism Design
Abstract: This paper discusses the implementation of the biological fish swimming motion onto the biomimetic fish robots. The mechanism designs and the control methodologies might vary as the fundamental knowledge is learnt from different species of fish. However, all those systems can be divided into two major types in general, namely: serial open chain design and parallel mechanism design from an engineering viewpoint. The general solutions to the swimming motion planning for the type with parallel mechanism are discussed by using the kinematics equations, followed by the derivation of analytical gait control functions. The application of these solutions on a manta fish prototype and an eight-joint MPF (media and/or paired fin) fish prototype shows the good agreement with the proposed modeling in the steady swimming and forward/backward swimming.

Keywords: Biomimetics, Marine Robotics
Abstract: This paper proposed a new method of designing a flexible biomimetic fish propelled by oscillating flexible pectoral fins. The molding soft body is adopted in the robotic fish. Pneumatic artificial muscles are utilized as driving sources and two ribs with distributed flexibility as main parts of the propulsive mechanism. The leading edge locomotion profile of the flexible pectoral fin in air is studied experimentally, and the flapping locomotion in water is observed too. Finally, the effectiveness of the proposed method is illustrated by the experiment. It shows that the robotic fish can realize self-driven, and it can swim at a speed of 0.18m/s~0.20m/s after optimization.

Keywords: Cognitive Human-Robot Interaction, Medical Robots and Systems, Human Performance Augmentation
Abstract: As medical robotics gathers increasing attention, the ergonomics of the surgical-console design becomes an important issue. Motivated by the need of augmenting the surgeon mastery, we explore the capabilities of a near infrared brain-computer interface as a complementary input modality to enhance the human-robot interaction at the robotic console. A multistage analysis framework is proposed and evaluated by an exploratory off-line synchronous study. The three stages of the data processing flow, namely dimensionality reduction, solution to binary problems and aggregation into multi-class decision are examined to address key challenges during the pattern recognition step. Early experimental results endorse near infrared based brain-computer interface as a suitable additional communication modality between the surgeon and the robotic console.

Keywords: Medical Robots and Systems, Neurorobotics
Abstract: In this paper, we present a novel robotic assistant dedicated to otologic surgery for an implantable hearing aid system, which is a procedure involving drilling into the lateral skull of the patient. This compact and flexible miniature robot is designed so as to fulfill the requirements of precise bone drillings for hearing aid implantation. It is built from an original five degree-of-freedom (DOF) parallel structure with a motorized end-effector, particularly well suited to otological surgical procedure. The specification, the design and the analysis of the workspace are detailed. A preliminary accuracy evaluation is presented. A rotational accuracy of 0.6 +/- 0.6 degree and a translational accuracy of 1.4 +/- 0.5 mm were found.

Keywords: Medical Robots and Systems
Abstract: We describe a control method, for a surgical robot, which prevents the overload at fragile tissues. In particular, we focused on the control parameter setting method to ensure the robustness of the performance relative to the variation of the organ stiffness parameter. Firstly, we present Position/ Limited Stress control to achieving both precise positioning and prevention of overload. FEM based organ model was used to estimate the stress in this control method. Secondly, we describe the control parameter setting method. The control parameter was set to realize sufficient performance within the range of stiffness variation. Finally, we carried out a numerical simulation and an in vitro experiment. The simulation result suggests that our control method and parameter setting method helps prevent stress overload, not depending on the stiffness of organ model . The in vitro experimental result suggests that our method helps prevent stress overload of the in vitro-liver, the stiffness parameter of which is unknown.

Keywords: Medical Robots and Systems, Dexterous Manipulation, Parallel Robots
Abstract: The development of a novel actuator driven laparoscopic instrument with parallel kinematic instrument tip serves to overcome the workspace restrictions of classic laparoscopic instruments and provides the surgeon multiple degrees of freedom (DOF) inside the patients body. First of all the requirements concerning control and motion have been derived in cooperation with medical partners. According to this, the aim of the project is to provide an intuitively controllable instrument especially suitable for laparoscopic dissection. It contains a 4-DOF movement at its intracorporeal side and can be one-hand-controlled by the surgeon. With 4 intracorporeal DOF it is possible to accomplish precision movements in a small intracorporeal workspace under different orientations. A parallel kinematic mechanism for the moving instrument tip has been designed. This paper describes the development of the mechanism topology and a numeric approach for the kinematic calculation. To drive the mechanism during tissue manipulation forces of up to 15 N are required. Only piezoelectric drives provide a sufficient power density regarding forces and speed. Hence traveling wave ultrasonic motors have been chosen. The position and velocity control of a single motor is presented as well as the entire instrument control structure containing trajectory planning of the surgeons input and the kinematic calculation. An intuitive control is assured by a 3-DOF joystick that can be controlled by the surgeon's thumb. A first prototype of the entire instrument has been successfully tested in an animal experiment.

Keywords: Range Sensing, Sensor Fusion, Wheeled Robots
Abstract: In this paper, we propose a novel human detecting system using several stationary and moving laser range finders(LRF). The occluded area where the stationary sensors cannot measure will be covered by the actively moving sensor. The occlusion is perceived by overlaying visible area of the stationary sensors. The moving sensor will move to the target position where the sensor can measure the occluded area. Finally, the measured information of all sensors will be merged for data fusion. The experimental results show the effectiveness of the system.

Keywords: Range Sensing, Intelligent Vehicles, Field Robots
Abstract: To increase autonomous ground vehicle (AGV) safety and efficiency on outdoor terrains the vehicle’s control system should have settings for individual terrain surfaces. A first step in such a terrain-dependent control system is classification of the surface upon which the AGV is traversing. This paper considers vision-based terrain surface classification for the path directly in front of the vehicle (< 1 m). Most visionbased terrain classification has focused on terrain traversability and not on terrain surface classification. The few approaches to classifying traversable terrain surfaces, with the exception of the use of infrared cameras to classify mud, have relied on stand-alone cameras that are designed for daytime use and are not expected to perform well in the dark. In contrast, this research uses a laser stripe-based structured light sensor, which uses a laser in conjunction with a camera, and hence can work at night. Also, unlike most previous results, the classification here does not rely on color since color changes with illumination and weather, and certain terrains have multiple colors (e.g., sand may be red or white). Instead, it relies only on spatial relationships, specifically spatial frequency response and texture, which captures spatial relationships between different gray levels. Terrain surface classification using each of these features separately is conducted by using a probabilistic neural network. Experimental results based on classifying four outdoor terrains demonstrate the effectiveness of the proposed methods.

Keywords: Range Sensing, Field Robots, Navigation
Abstract: Scanning laser range sensors (ladars) are frequently used in mobile robotics applications because their ability to accurately measure the environment in 3D makes them well-suited for perception tasks like terrain modeling and obstacle detection. The choice of ladar sensor and the manner in which it is configured and integrated into a robot platform is usually determined subjectively based on the experience of the project team members. This paper develops a method for evaluating ladar sensors and sensor configurations that objectively measures the quality of a sensor/configuration choice in terms of density and uniformity of measurements within a region of interest. The method is applicable to static sensors and environments as well as scenarios with moving objects and mobile sensors. It can be used to compare different sensors, to evaluate specific sensor configurations and search for the optimal one, and to aid in designing new ladar sensors tailored to specific applications. We find that popular ladar configurations are often not the best configuration choice, and that alternative configurations not commonly used would offer better data density and uniformity.

Keywords: Range Sensing, Visual Tracking, Recognition
Abstract: Laser based tracking systems have been developed for mobile robotics and intelligent surveillance areas. Existing systems estimate only human positions. In this paper, we propose a method for human pose estimation represented by human head and waist position using only laser range finders. Two features of human cross-sectional contours are extracted from laser scanner data scanning on the height of waist. This method estimates human pose by using these features in the Bayesian filtering framework. Moreover, we develop a new particle filter framework with two transition models and two resampling steps. In this framework, position estimation and pose estimation are performed by many candidates. Our experimental results demonstrate the effectiveness of the method in pose estimation of multiple people by using only several laser scanners.

Keywords: Sensor Networks, Legged Robots, Dynamics
Abstract: We report on a 12-axis accelerometer suite which utilizes 12-axis linear acceleration measurements from four 3-axis accelerometers. This system is capable of deriving linear acceleration, angular acceleration and angular velocity via simple matrix operations. It also releases the requirement of accelerometer installation at the center of mass as well as eliminates the necessity of gyro implementation as in the traditional inertia measurement unit (IMU). An optimal configuration of the system is proposed based on the analysis of rigid body dynamics and matrix theory. We also report the results of experimental evaluation. We believe the analysis presented in this paper would benefit the practical design of IMUs in the future.in the future.

Keywords: Sensor Fusion, Visual Tracking, Range Sensing
Abstract: The power management system for autonomous mobile robots is an important issue for keeping robots in their long-time functionality. Recharging is necessary before the power of the robot has exhausted. In this paper, we propose a multi-sensor fusing method using intensity and range data fusion with covariance intersection approach to locate the robot pose while performing the docking for recharging. An artificial landmark is employed as a visual cue on a docking station in order to recognize the location by using inverse perspective projection. At the same time, the range data acquired by laser range finder are modeled as multiple line segments which are the hypothetical walls in the environment. Then the geometrical relationship between the robot and the docking station is estimated much more precisely by using covariance intersection approach. We have demonstrated the success of the proposed algorithms through experimental results.

Keywords: Sensor Networks, Path Planning for Multiple Mobile Robot Systems
Abstract: In this paper, we study the problem of optimal trajectory generation for a team of mobile robots tracking a moving target using distance and bearing measurements. Contrary to previous approaches, we explicitly consider limits on the robots' speed and impose constraints on the minimum distance at which the robots are allowed to approach the target. We first address the case of a single sensor and show that although this problem is non-convex with non convex constraints, in general, its optimal solution can be determined analytically. Moreover, we extend this approach to the case of multiple sensors and propose an iterative algorithm, Gauss-Seidel-relaxation (GSR), for determining the set of feasible locations that each sensor should move to in order to minimize the uncertainty about the position of the target. Extensive simulation results are presented demonstrating that the performance of the GSR algorithm, whose computational complexity is linear in the number of sensors, is indistinguishable of that of a grid-based exhaustive search, with cost exponential in the number of sensors, and significantly better than that of a random, towards the target, motion strategy.

Keywords: Sensor Networks, Calibration and Identification
Abstract: We present the design and implementation of a new jumping robot for mobile sensor network. Unlike other jumping robots, the robot is based on a simple two-mass-spring model. After we throw it on ground, it can stabilize itself and then jump once. The detailed mechanism design including the load holding and self-stabilization are presented. Jumping heights and distances with different robot weights are measured and compared with calculated values from the two-mass-spring model.

Keywords: Micro/Nano Robots, Biomimetics, Smart Actuators
Abstract: In our previous study, we first succeeded in construction of a novel-types self-oscillting molecular robot. However, the driving environment of the molecular robot was firmly restricted in the strong acid condition. This is because the molecular robots drive induced by the Belousov-Zhabotinsky (BZ) reaction, which is well known for exhibiting temporal and spatiotemporal oscillating phenomena. The overall process of the BZ reaction is the oxidation of an organic substrate, such as malonic acid (MA) or citric acid, by an oxidizing agent (bromate ion) in the presence of a strong acid and a metal catalyst. In this study, in order to drive the novel molecular robot under the physiological condition, we conducted the modification of the molecular structure of the self-oscillating polymer chain. In order to cause the self-oscillation under the biological condition, we synthesized a built-in system where the BZ substrates other than organic acid were incorporated into the molecular robot itself. As a result, the novel molecular robot drives under the biological condition. We believe that the development of the novel molecular robot lead to construction of the novel biomimetic soft robots and actuators, and may inspire novel nonlinear experimental and theoretical considerations.

Keywords: Biologically-Inspired Robots, Biomimetics, Search and Rescue Robots
Abstract: For a new class of soft robotic platforms, development of flexible and robust actuators is quintessential. Remarkable resilience, shape memory effect, high energy density, and scalability are attributed to nickel titanium (NiTi) making it an excellent actuator candidate for meso-scale pplications. This paper presents a micro-muscle fiber crafted from shape memory alloy (NiTi) coiled springs. An enhanced spring NiTi model describes the combination of martensite deformation and spring effect due to its geometry. This paper also describes a manufacturing process and characterization for micro-scale NiTi coil actuators in various annealing temperatures. The presented fiber is 400um in diameter and 0.5m in length exhibiting 50% contraction and 1226J=kg of energy density with 40g of force. By changing the geometry of the spring, force-displacement characteristics can be tuned. An enhanced-performance inverted-spring manufacturing method is also described and characterized. A method of discrete displacement control is presented. Taking advantage of the flexibility of micro-coil spring, we present a novel mesh-worm prototype that utilizes bio-inspired antagonistic actuation for its body deformation and locomotion.

Keywords: Biomimetics, Service Robots, Biologically-Inspired Robots
Abstract: This paper proposes a neural oscillator based control to attain rhythmically dynamic movements of a robot arm. In human or animal, it is known that neural oscillators could produce rhythmic commands efficiently and robustly under the changing task environment. In particular, entrainments of the neural oscillator play a key role to adapt the nervous system to the natural frequency of the interacted environments. Hence, we discuss how a robot arm controls for exhibiting natural adaptive motions as a controller employing the entrainment property. To demonstrate the excellence of entrainment, we implement the proposed control scheme to a real robot arm. Then this work shows the performance of the robot arm coupled to neural oscillators in various tasks that the arm traces a trajectory. Exploiting the neural oscillator and its entrainment property, we experimentally verify an impressive capability of self-adaptation of the neural oscillator that enables the robot arm to make adaptive changes corresponding to an exterior environment.

Keywords: Biologically-Inspired Robots, Biomimetics, Neurorobotics
Abstract: We present a novel biomimetic approach to mapless autonomous navigation based on insect neuroethology. We implemented and tested a real-time neuronal model based on the Distributed Adaptive Control framework. The model unifies different aspects of insect navigation and foraging including landmark recognition, chemical search, path integration and optimal memory usage. Consistent with recent findings the model supports navigation using heading direction information, thus precluding the use of global information. We tested our model using a mobile robot performing a foraging task. While foraging for chemical sources in a wind tunnel, the robot memorizes the followed trajectories, using information from landmarks and heading direction accumulators. After foraging, landmark navigation is tested with the odor source turned off. Our results show stability against robot textit{kidnapping} and generalization of homing behavior to stable mapless landmark navigation. This demonstrates that allocentric and efficient goal-oriented navigation strategies can be generated by relying on purely local information.

Keywords: Mechanism Design, Multifingered Hands
Abstract: We propose a load sensitive Continuously Variable Transmission (CVT) for a wire-driven robot hand “Drum CVT”, and aims at achieving efficient finger motions by mechanically changing the reduction rate of the drive: fast finger motion with low load (i.e., low drive at fast motion) and slow finger motion with high load (i.e., high drive at slow motion). We developed two material types of Drum CVT: the deflection-type (using nylon) and the torsion-type (using metal). Both types are investigated in both theoretical and actual models, and demonstrated their performance. Eventually, we revealed those characteristics, and indicated the usage of each Drum-CVT.

Keywords: Multifingered Hands, Dexterous Manipulation, Grasping
Abstract: This paper proposes a stable object grasping method to realize dynamic force/torque equilibrium by using a triple robotic fingers system with soft and deformable hemispherical fingertips. In the authors' previous works, ``Blind Grasping'' control scheme, which realizes stable object grasping without use of any external sensing such as vision, force, or tactile sensing in the case of using a pair of robot fingers, has been proposed. This control methodology is based on a unique configuration of human hand, called ``Fingers-Thumb Opposability''. In this paper, a ternary finger in addition to a pair of fingers is introduced not only to expand a stable region of grasping, but also to enhance dexterity and versatility of the multi-fingered robotic hand system. To this end, a ``Blind Grasping'' manner is modified in order to install it in the triple fingers system. First, dynamics of the triple robotic fingers system and a grasped object with considering rolling constraints is modeled, and a control input based on the blind grasping manner is designed. Next, the closed-loop dynamics is derived and a stability analysis is shown briefly. Finally, its usefulness is discussed through numerical simulation results.

Keywords: Multifingered Hands, Dexterous Manipulation, Grasping
Abstract: This paper proposes a novel control method for stable grasping using a multi-fingered hand-arm system with soft hemispherical finger tips. The proposed method is simple but easily achieves stable grasping of an arbitrary polyhedral object using an arbitrary number of fingers. Firstly, we formulate nonholonomic constraints between a multi-fingered hand-arm system and an object constrained by rolling contact with finger tips, and derive condition for stable grasping by stability analysis. A new index for evaluating the possibility of stable grasping is proposed and efficient initial relative positions between finger tips and the object for realizing stable grasping are analyzed. The stability of the proposed system and the validity of the index are verified through numerical simulations.

Keywords: Multifingered Hands
Abstract: Humanoid robots and robotic manipulators with good dexterity are promising to enhance the factory productivity in next generation. Dexterity of robotic manipulators can be achieved by equipping an anthropomorphic robot hand with multiple fingers. Additionally, in order to manipulate various tools that humans are using in daily life, the size and the exerting force of the robot hand should be similar to that humans are. In this paper, we proposed a human-sized multi-fingered robot hand with detachable mechanism at the wrist. The robot hand can be split at the wrist into the hand part and the actuator part. The fingers are driven by wires and are controlled by actuators embedded in the arm part. The driving force from the arm part is transmitted to the hand part by gear mechanism at the wrist. The developed robot hand has the size of 200[mm](length) x 78[mm](width) x 24.6[mm](thickness) and can exert 10[N] at the fingertip. The performance of the developed robot hand was shown by a motion control experiment.

Keywords: Recognition, Learning and Adaptive Systems, Humanoid Robots
Abstract: This paper describes a step-size parameter adaptation technique of multi-channel semi-blind independent component analysis (MCSB-ICA) for a ``barge-in-able'' robot audition system. By ``barge-in'', we mean that the user can speak simultaneously when the robot is speaking. We focused on MCSB-ICA to achieve such an audition system because it can separate a user's and a robot's speech under reverberant enritonments. The problem with MCSB-ICA for robot audition is the slow speed of convergence in estimating a separation filter due to its step-size parameters. Many optimization methods cannot be adopted because their computational costs are proportional to the 2nd order of the reverberation time. Our method yields adaptive step-size parameters with MCSB-ICA at low computational costs. It is based on three techniques; 1) recursive expression of the separation process, 2) a piecewise linear model of the step-size of the separation filter, and 3) adaptive step-size parameters with a sub-ICA-filter. Experimental results show that our approach attains faster convergence speed and lower computational costs than those with a fixed step-size parameter.

Keywords: Marine Robotics, Voice, Speech Synthesis and Recognition, Recognition
Abstract: The project ASAROME (Autonomous SAiling Robot for Oceanographic MEasurements) is working on a small autonomous sailboat in order to make measurements and observations in the marine environment for long periods. In this project, perception plays an important role by giving an estimate of the speed of surface winds, the state of the sea surface and the rate of precipitation in wet weather. In this paper, the unknown signals are first encoded with different codes (ERB, MFCC, LPC, LPCC). Then the coded signals are modeled by two different methods of classification: predictive and k-Nearest Neighbor. The final part of the system uses local and global decision to recognize the class of the unknown signal. Experiments are conducted to compare the results obtained by different encodings. Our results show that MFCC does not represent the ideal approach for the recognition of underwater audio signals, but LPCC seems to be a better candidate.

Keywords: Entertainment Robotics, Recognition, Humanoid Robots
Abstract: We aim at developing a singer robot capable of listening to music with its own “ears” and interacting with a human’s musical performance. Such a singer robot requires at least three functions: listening to the music, understanding what position in the music is being performed, and generating a singing voice. In this paper, we focus on the second function, that is, the capability to align an audio signal to its musical score represented symbolically. Issues underlying the score alignment problem are: (1) diversity in the sounds of various musical instruments, (2) difference between the audio signal and the musical score, (3) fluctuation in tempo of the musical performance. Our solutions to these issues are as follows: (1) the design of features based on a chroma vector in the 12-tone model and onset of the sound, (2) defining the rareness for each tone based on the idea that scarcely used tone is salient in the audio signal, and (3) the use of a switching Kalman filter for robust tempo estimation. The experimental result shows that our score alignment method improves the average of cumulative absolute errors in score alignment by 29% using 100 popular music tunes compared to the beat tracking without score alignment.

Keywords: Entertainment Robotics, Humanoid Robots, Service Robots
Abstract: We propose a Thereminist robot system that plays the Theremin based on a Theremin's pitch model. The Theremin, which is a 1920s electronic musical instrument, is played by moving a player's hand position in the air without touching it. It is difficult to play the Theremin because the relationship between the hand position and Theremin's pitch (pitch characteristics) is non-linear and varies according to the electromagnetic feld (hereafter called environment). These characteristics cause two problems: (1) Adapting to the environment change is required and (2) a naive design tends to depend on robot's particular hardware. We implement the coarse-to-fne control system on the Thereminist robot using newly proposed two pitch models: parametric and nonparametric ones. The Thereminist robot works as below: frst, the robot calibrates the pitch model by parameter ftting with the Levenberg-Marquardt method. Second, the robot moves its hand in a coarse manner by feedforward control based on the pitch model. Finally, the robot adjusts its position by feedback control (Proportional-Integral control). In these steps, the robot can play a required pitch quickly, because the robot moves its hand using the pitch model without listening to the Theremin's sound Thus, the time to play the exact pitch is shorter than when only feedback control is used. Three experiments were conducted to evaluate the robustness against the number of samples, environment change, and types of robots. The results revealed that our pitch model describes using only 12 samples of pitches for estimation of the parameters, and adapts if the environment changes. In addition, our system works on two different robots: HRP-2 and ASIMO.

Keywords: Entertainment Robotics, Voice, Speech Synthesis and Recognition, Social Human-Robot Interaction
Abstract: The Waseda Flutist Robot is able to play the flute at the level of an intermediate human player. This ability opens a wide field of possibilities to research human-robot musical interaction. This research is focused on enabling the flutist robot to interact more naturally with musical partners in the context of a Jazz band. For this purpose a Musical-Based Interaction System (MbIS) has been proposed to enable the robot to process both visual and aural cues coming throughout the interaction with musicians. In a previous publication, we have concentrated on the implementation of visual communication techniques. We created an interaction interface that enabled the robot to detect instrument gestures of partner musicians during a musical performance. Two computer vision approaches were implemented to create a two-skill-level interface for visual human-robot interaction in a musical context. In this paper we focus on the aural perception system of the robot. The method introduced here enables the robot to, a suitable environment provided, detect the tempo and harmony of a partner musician’s play, with a specific focus on improvisation. We achieve this by examining the rhythmical and harmonic characteristics of the recorded sound. We apply the same approach to amplitude and frequency spectrum, thus, in the former case tracking amplitude transients. In the latter case, as we focus on communication with monophonic woodwind instruments, we follow the most prominent peak in the frequency spectrum. We specifically use a similar technique for the audio analysis as we did for our previous research on motion tracking. From the experimental results, we have shown that after implementing our algorithm the robot is able to correctly recognize a number of rhythms and harmonies. It is able to engage in a simple form of stimuli and reaction play with a human musician.

Keywords: Entertainment Robotics, Biologically-Inspired Robots, Humanoid Robots
Abstract: During several decades, the research at Waseda University has been focused on developing anthropomorphic robots able of performing musical instruments. More recently, the authors have succeeded in developing a human-like robot able of playing the alto saxophone. As a result of our research efforts, the Waseda Flutist Robot WF-4RIV and the Waseda Saxophonist Robot WAS-1 have been designed to reproduce the human player performance. Therefore, as a long-term goal, we are proposing to enable the interaction between musical performance robots (i.e. robots orchestra). Such approach may enable us not only to propose new ways of musical expression, but also we may contribute to the better understanding of some of the mechanisms that enable the communication of humans in musical terms. In general terms, the communication of humans within an orchestra is a special case of conventional human social behavior. Rhythm, harmony and timbre of the music played represent the emotional states of the musicians. Of course, we are not considering a musical performance robot (MPR) just as a mere sophisticated MIDI instrument. Instead, its human-like design and the integration of perceptual capabilities may enable to act on its own autonomous initiative based on models which consider its own physical constrains. Due to the complexity of our long-term goal, in this paper, we are presenting our first steps towards enabling the interaction between musical performance robots. In particular, the details of the musical performance control systems are detailed. Thanks to the use of MIDI data, we performed preliminary experiments to enable a duet performance between the WF-4RIV and the WAS-1. We expect in the future; as a result of our research, we may enable a single anthropomorphic robot to perform different kinds of woodwind instruments as well as enable to interact at with level of perceptual capabilities (like human does).

Keywords: Entertainment Robotics, Service Robots, Dexterous Manipulation
Abstract: This paper describes a method to generate stroke trajectories executed by a 5-DOF robotic art system. A brush footprint model is proposed to represent the footprint outline, which is sensitive to the applied stress. After extracting real brush footprints from experiments, the model parameters are obtained using linear regression. Trajectories are searched along the segmented strokes of Chinese characters by varying the shape of brush footprint. The generated trajectory is 5-DOF, which is compatible to the robot art system. Simulations and experiments were conducted using calligraphy of Bada Shanren, a famous Chinese ancient artist, as an example.

Keywords: Entertainment Robotics, Motion Control, Navigation
Abstract: The paper describes the control and the navigation of a skiing robot that is capable of autonomous skiing on a ski slope using the carving skiing technique. Based on a complex sensory system it is capable of autonomous navigating between the race gates, avoiding obstacles and maintaining a stable position during skiing on an previously unknown ski slope. The robot was tested on different ski slopes with various race gates combination.

Keywords: Education Robotics
Abstract: The reported work advances the state-of-the-art in assistive technology for the blind by enhancing a low-cost automated tutor designed to teach braille writing skills to visually impaired children using voice feedback. We first provide some background on how the methodology of Intelligent Tutoring Systems correlates to an automated tutor for teaching braille writing skills. We then build on prior work to enhance our automated Braille Writing Tutor in three dimensions: (1) Initial field testing in three different countries; (2) Exploring customization needs for improving relevance in different cultures; and (3) Adding relevant games for increasing motivation. The outcome of this work is an enhanced low-cost tool that can help to increase braille literacy in blind communities around the world.

Keywords: Education Robotics, Control Architectures and Programming, Networked Robots
Abstract: One of the main challenges when creating an undergraduate introduction to robotics course is connecting the theory taught in the lectures with the current practices of research. The primary cause of this difficulty is an inability to find a hardware solution that is powerful enough to run complex cutting-edge algorithms yet inexpensive enough to be purchased by an undergraduate class budget. An ideal system needs to have a gentle learning curve to allow students with minimal background in the field to get a robot up and running. Lastly, a fleet of classroom robots needs to be easy to administrate and maintain given the limited time of a Teaching Assistant. Our approach is to implement a centralized server system. In this system individual robots are inexpensive yet capable of establishing a WiFi link to a main server so that all the compilation and system administration, as well as much of the computationally intensive processing, are done on that server. We find that this solution saves both time and money and provides an effective teaching tool. This paper describes the hardware and software architecture of the system, and example applications implemented by undergraduate students.

Keywords: Education Robotics
Abstract: We propose a novel robotic developmental kit for educational purpose. It helps junior high / high school / university students to understand recent prosthetic technology and, moreover, to provide a chance to produce creative prosthetic applications for short time at low cost. The developmental kit consists of an EMG-to-Motor controller and a wire-driven device. For delivering the cheapness and easiness to students, we demonstrate three prosthetic applications based on the kit: (1) Simple Prosthetic Hand is a mimic of commercial prosthetic hand. It illustrates that low-precise design achieves cheap production cost and sufficient function as a prosthetic hand. (2) Rock-Scissors-Paper Prosthetic Hand is based on prosthetic hands for research use. It clearly illustrates EMG-to-Motion discrimination processes by displaying real signals. (3) EMG Presbyopia Spectacles shows the possibility that beginners design creative prosthetic applications based on daily activities. Finally, we report two educational courses we have conducted for junior high and high school students.

Keywords: Education Robotics, Wheeled Robots, Mechanism Design
Abstract: The rapidly increase of personal robotic platforms and their applications in Japan represents a great challenge for universities to introduce undergraduate students the basic knowledge required to develop intelligent automated mechanisms. For this purpose; in this paper, we are presenting our approach to introduce first year undergraduate students of the Department of Modern Mechanical Engineering the basics of robotics systems. In order to foster the creativity of undergraduate students of engineering fields, we focused in developing an education tool designed to introduce at different educational levels the principle of developing mechatronic systems. In particular, the development of an inverted pendulum mobile robot Waseda Wheeled Vehicle No. 2 (WV-2R) has been proposed. Different kinds of experiments were proposed to confirm the possibility of implementing controllers as well as changing physical properties of the system to observe differences on the response of the system. From the experimental results, we could confirm the effectiveness of the proposed systems to control the angle of pendulum respect to the body base as well as by changing the radius of the wheel.

Keywords: Space Robotics
Abstract: In this paper, the control problem of space robot system with uncertain parameters and external disturbances is discussed. With the momentum conservation of the system, the kinematics and dynamics of the system are analyzed, and it is found that the generalized Jacobi matrix and the dynamic equations of the system are nonlinearly dependent on inertial parameters. In order to overcome the problems mentioned above, the idea of augmentation approach is introduced. It is shown that the augmented generalized Jacobi matrix and the dynamic equations of the system can be linearly dependent on a group of inertial parameters with augmented inputs and outputs. Based on the results, a robust adaptive composite control scheme for space-based robot to track the desired trajectories in inertial space is developed. The stability of the overall system is analyzed through Lyapunov direct method. For the proposed approach, the global uniform asymptotic stability of the system is established. In addition, the controller presented possesses the advantage that it needs no measurement of the position, linear velocity and acceleration of the base with respect to the orbit, because of the effective exploitation of the particular property of system dynamics. To show the feasibility of control scheme, a planar space robot system is simulated.

Keywords: Space Robotics, Adaptive Control, Dynamics
Abstract: This paper proposes an adaptive controller for a fully free-floating space robot with kinematic and dynamic model uncertainty. In adaptive control design for the space robot, because of high dynamical coupling between an actively operated arm and a passively moving end-point, two inherent difficulties exist, such as non-linear parameterization of the dynamic equation and both kinematic and dynamic parameter uncertainties in the coordinate mapping from Cartesian space to joint space. The proposed method in this study overcomes the above two issues by paying attention to the coupling dynamics. The proposed adaptive controller does not involve any measurement of acceleration; but it is still possible for the system to be linearly parameterized in terms of uncertain parameters and a suitable input torque can be generated in the presence of model uncertainty. A numerical simulation was carried out to confirm the validity of the proposed adaptive control.

Keywords: Space Robotics, Path Planning for Manipulators, Dexterous Manipulation
Abstract: This paper focuses on the guidance of a robot manipulator to capture a tumbling satellite and then bring it to state of rest (detumbling). First, a coordination control for combined system of the space robot and the target satellite, which acts as the manipulator payload, is presented so that the robot tracks the optimal path while regulating the attitude of the chase vehicle to a desired value. Subsequently, two optimal trajectories for the pre- and post-capture phases are designed. In the pre-capturing phase, the manipulator maneuvers are optimized by minimizing a cost function which includes the time of travel and the weighted norms of the end-effector velocity and acceleration, subject to the constraint that the robot end-effector and a grapple fixture on the satellite arrive at the rendezvous point with the same velocity. In the post-grasping phase, the manipulator dumps the initial velocity of the tumbling satellite in minimum time subject to the constraint that the magnitude of the torque applied to the satellite remains below a safe value. Simulation and experimental results are appended.

Keywords: Space Robotics, Intelligent Vehicles, Navigation
Abstract: The wheels of planetary rovers that are used in space explorations sometimes slip or lose contact with the ground while traversing a sandy terrain. In order to estimate the behavior of these rovers moving on loose soil, it is very important to accurately estimate the drawbar pull of their wheels. Some wheel-soil interaction models based on terramechanics have been proposed for the estimation of the normal stress distribution and drawbar pull of such rovers. However, our experimental results (normal stress distributions are directly measured using a pressure sensor array, which is attached to the wheels of a rover) show that the distribution range of normal stress for small wheeled rovers obtained using the proposed method is considerably smaller than that obtained by using conventional method. Consequently, the drawbar pull estimated using conventional methods is inaccurate. Therefore, in this study, the normal stress distribution is directly measured using pressure sensors in order to estimate drawbar pull accurately. From the data obtained using the sensors, a soil parameter, which is generally very difficult to measure, is estimated. Then, the drawbar pull is estimated using this parameter. The drawbar pull estimated by using the proposed method is more accurate than that estimated using conventional methods. In this study, we propose a new method for the estimation of drawbar pull and also validate this method.

Keywords: Service Robots, Smart Actuators, Kinematics
Abstract: We present pipe inspection robot using newly developed spherical ultrasonic motor (SUSM) as a camera actuator. Because the SUSM is very small and has three rotational degrees of freedom (DOF), the robot using SUSM can be inserted to the inside of pipe of 50 mm in diameter. The novel SUSM has improved the range of movement compared to previous SUSM and the robot can point a camera in any direction. In this paper, we determined a method of rotational direction and control strategy from the kinematics and characteristics of ultrasonic motor. The rotational directions were defined by the phase differences of applied voltages, and the rotational speed were changed by the frequencies. Additionally, we developed a very small position sensing system using rotary potentiometers. In the control experiment using the sensing system, the SUSM have shown the returnability to the default position within 1 degree of accuracy from several specified points.

Keywords: Field Robots, Biologically-Inspired Robots, Robotics in Agriculture and Forestry
Abstract: Modules have been widely used in the development of re-configurable robots and snake-like robots. Modularization methodology can actually be applied in design of other robots. To build robotic systems flexibly and quickly with low costs of manufacturing and maintenance, we have developed two basic types, which we call I-type and T-type, of joint modules and several functional modules including grippers, suckers and wheels/feet, for building new robotic systems. In this paper, we introduce the design of the basic joint and functional modules, and present several novel robotic systems built in the modularization methodology using these modules. Specifically, we show how to develop these modules and use them to set up a manipulator, a 6-DoF biped walking robot, a wheeled mobile robot, a biped tree-climbing robot, and a biped wall-climbing robot. It has been shown that a few joint modules and functional modules can easily spawn a variety of novel robots with unique features.

Keywords: Mechanism Design, Underactuated Robots, Multifingered Hands
Abstract: Modular design problems and requirements for underactuated mechanisms are discussed as related to robotic fingers. The proposed modular mechanism is connected sequentially by units of underactuated mechanisms, with the aim of self-adaptive grasp operation. Design considerations for modular underactuated mechanism are outlined and optimality criteria are analyzed with the aim to formulate a general design algorithm. An example of a four-phalanx modular robotic finger is studied as an improvement for LARM Hand in order to show the practical feasibility of the proposed modular concept and design procedure.

Keywords: Service Robots, Adaptive Control, Flexible Arms
Abstract: The paper presents a DSP/FPGA based multi-sensory flexible-joint robot including modular mechanics, hardware and software architecture. The robot is composed of four modular flexible joints and one DLR-HIT-Hand. In each joint there is a Field Programmable Gate Array (FPGA) for sensor data processing, brushless DC motor control and communication. The kernel of the hardware system is a PCI-based high speed floating-point Digital Signal Processor (DSP) for the arm/hand Cartesian level control, and FPGA for two high speed (up to 25 Mbps) real-time Serial Buses communication with the arm and hand. All the electronics are integrated into the joint to achieve high modularity and reliability. Cartesian impedance control and position control with on-line gravity compensation are realized for regulation tasks of the robot with elastic joints. In addition, the experiments of the joint impedance control and Cartesian impedance control demonstrate that the multi-sensors highly integrated robot has a good performance.

Keywords: Motion Control
Abstract: An adaptive cruise control (ACC) which was implemented on an AIT Intelligent Vehicle, a Mitsubishi Galant car, has been improved and added with more features to allow the vehicle to act with better performance compared with the previous system. An important feature of the new adaptive cruise control system is the ability to maintain a proper inter-vehicle gap based on the speed of leading vehicle and time headway (THW). To develop adaptive cruise control system, the conventional throttle valve system is modified to the drive-by-wire system which uses a DC motor to control the throttle valve position based on PD control with command compensation. In the automatic braking system, a DC motor is installed with steel cable transmission in order to pull the brake pedal to the desired level automatically by applying torque control. The brake control and velocity control have been merged together to control the speed to any desired speeds as fast as possible without jerk and steady-state error. A micro switch is installed at the brake pedal to allow the driver to take over the control of the vehicle anytime. There are three important inputs of the ACC system, speed of leading vehicle read from electronic control unit (ECU), THW set by driver, and actual gap measured from a laser scanner. The ACC processes these three inputs in order to calculate distance error and relative velocity which are used as the two inputs of a fuzzy controller. The fuzzy controller determines the desired speed command to maintain a proper gap based on current speed of the leading vehicle and the desired time headway. Experiments are conducted to evaluate the performance of the ACC system in various conditions. The results show good performance of the adaptive cruise control system.

Keywords: Distributed Robot Systems, Cooperating Robots, Adaptive Control
Abstract: Division of Labor Control is advanced function for distributed autonomous robotic systems. Many studies focussing division of labor control inspired biological phenomenon have been reported. However, the optimality is not discussed because decentralized control is typically complicated. In this study, we propose the division of labor control method for robot group that enable adaptively select whether homogeneous state or heterogeneous state against working conditions and address the optimality by mathematical analysis. To evaluate the effectiveness of the proposed method, the computer simulations are carried out and we confirm that robot group implemented the proposed method inevitably organize the division of labor state with group performance improvement.

Keywords: Cognitive Human-Robot Interaction, Recognition, Physical Human-Robot Interaction
Abstract: In this paper, we propose an online hand gesture recognition algorithm for a robot assisted living system. A neural network-based gesture spotting method is combined with the hierarchical hidden Markov model (HHMM) to recognize hand gestures. In the segmentation module, the neural network is used to determine whether the HHMM-based recognition module should be applied. In the recognition module, Bayesian filtering is applied to update the results considering the context constraints. We implemented the algorithm using an inertial sensor worn on a finger of the human subject. The obtained results prove the accuracy and effectiveness of our algorithm.

Keywords: Biomimetics, Biologically-Inspired Robots, Cellular and Modular Robots
Abstract: Despite its appealing concept, a systematic way of designing autonomous decentralized control system is still lacking. In order to alleviate this, we have so far proposed a design scheme for local sensory feedback control based on so-called ``discrepancy function" that extracts the discrepancies between body (i.e., mechanical system), brain (i.e., control system) and environments. This paper intensively investigates the validity of this design scheme by taking a two-dimensional serpentine robot exhibiting undulatory creeping locomotion as a practical example. Preliminary simulation results derived strongly indicate that our design methodology allows us to endow the robot with highly adaptability and fault tolerance. These results obtained are expected to shed a new light on design methodology for autonomous decentralized control system. Furthermore, together with a validity verification of the simulation results, this paper introduces a real two-dimensional serpentine robot that is currently under development.

Keywords: Nonholonomic Motion Planning, Navigation, Motion Control
Abstract: This paper presents an approach to time-optimal kinodynamic motion planning for a mobile robot. A global path planner is used to generate collision-free straight-line paths from the robot's position to a given goal location. With waypoints of this path, an initial trajectory is generated which defines the planned position of the robot over time. A velocity profile is computed that accounts for constraints on the velocity and acceleration of the robot. The trajectory is refined to minimize the time needed for traversal by an any-time optimization algorithm. An error-feedback controller generates motor commands to execute the planned trajectory. Quintic Bézier splines are used to allow for curvature-continuous joins of trajectory segments, which enables the system to replan trajectories in order to react to unmapped obstacles. Experiments on real robots are presented that show our system's capabilities of smooth, precise, and predictive motion.

Keywords: Nonholonomic Motion Planning, Path Planning for Manipulators
Abstract: Sampling-based motion planners are often used to solve very high-dimensional planning problems. Many recent algorithms use projections of the state space to estimate properties such as coverage, as it is impractical to compute and store this information in the original space. Such estimates help motion planners determine the regions of space that merit further exploration. In general, the employed projections are user-defined, and to the authors' knowledge, automatically computing them has not yet been investigated. In this work, the feasibility of offline-computed random linear projections is evaluated within the context of a state-of-the art sampling-based motion planning algorithm. For systems with moderate dimension, random linear projections seem to outperform human intuition. For more complex systems it is likely that non-linear projections would be better suited.

Keywords: Nonholonomic Motion Planning
Abstract: A new, simple, and fast method to compute the sharpness and curvature of a clothoid segment of a continuous curvature path is presented. When generating continuous curvature paths, clothoid segments are needed to connect straight segments to perfect arc segments. This algorithm is part of a new trajectory generator and motion planner that generates smooth, natural, drivable paths, using a minimal amount of steering to reach the desired ending position similar to the way a human would drive.

Keywords: Nonholonomic Motion Planning, Underactuated Robots, Motion Control
Abstract: In this paper, we propose a new example of nonholonomic mobile robot, which we call "the surface walker". This robot is composed of a hemisphere-shaped shell and and a 2-d.o.f. mass-control device (pendulum) inside it. We assume a nonholonomic rolling contact constraint, i.e., there is no slip at the contact point between the hemispherical sphere and the flat floor. Our purpose is to realize locomotion control of the robot by appropriately actuating the internal pendulum.

First, we derive a mathematical model of the whole system and investigate its locomotion principle (how to make the robot move in the desired direction) from a viewpoint of nonlinear controllability analysis. The controllability structure of the robot is essentially similar to that of "rolling-sphere manipulation problem", in which the control objective is to maneuver a rigid sphere to arbitrary configuration (position and orientation) under non-slip constraint. Bsed on this observation, we propose a periodic control method by extending the result of trajectory planning for rolling sphere problem. The resulting locomotion will be a distinctive "swaying-like" motion. Effectiveness of the proposed idea is demonstrated by numerical simulations and control experiments.

Keywords: Path Planning for Manipulators, Cooperative Manipulators
Abstract: This paper presents a novel approach for trajectory planning of multiple robot manipulators operating amongst obstacles. Karush-Kuhn-Tucker (KKT) conditions are exploited to compute the proximity between line-swept sphere (LSS) bounding volumes used to model potentially colliding objects. The KKT multipliers and the parameters giving the minimum distance between LSS volumes are augmented into the manipulator trajectory planning problem as dummy control variables. These extra variables allow the planning problem to be cast as a standard nonlinear optimal control problem with smooth path constraints, which is then solved using the pseudospectral method. The utility of the approach is demonstrated by a trajectory planning example involving stationary workspace obstacles and for a centralized multi-robot system in which each robot acts as a dynamic obstacle that the other should avoid. The optimal control formulation incorporates practical constraints on the manipulator joint angles, velocities and accelerations as well as limits on the control torque. The computed collision-free optimal trajectories are executed on a pair of experimental robots to verify the feasibility of the numerical results.

Keywords: Path Planning for Manipulators, Manipulation Planning, Dexterous Manipulation
Abstract: The main objective of this paper is to develop an autonomous navigation system for robot arms so that they can operate in complex environments, such as kitchen, factory, etc. In order to solve the problem of planning in the dynamic environments, we proposed a CT-RRTs (Bi-direction RRTs in Configuration Time space) planner, which can make the robot arm reach goal successfully in the partially known dynamic environment while remains the greedy heuristics of the RRT-Connect. It is planned in the augmented state-time space of the robot arm configuration and the positions of the moving objects. Various techniques are used to accelerate planning and enhance its safety. We used the new planner to develop the dual-arm planner, and it can be used as the basis to solve higher level problems in motion planning. The experiments show that the proposed method can effectively resolve the dual-arm motion planning problem.

Keywords: Path Planning for Manipulators, Humanoid Robots, Manipulation Planning
Abstract: In this paper, we present efficient solutions for planning motions of dual-arm manipulation and re-grasping tasks. Motion planning for such tasks on humanoid robots with a high number of degrees of freedom (DoF) requires computationally efficient approaches to determine the robot’s full joint configuration at a given grasping position, i.e. solving the Inverse Kinematics (IK) problem for one or both hands of the robot. In this context, we investigate solving the inverse kinematics problem and motion planning for dual-arm manipulation and re-grasping tasks by combining a gradient-descent approach in the robot’s pre-computed reachability space with random sampling of free parameters. This strategy provides feasible IK solutions at a low computation cost without resorting to iterative methods which could be trapped by joint-limits. We apply this strategy to dual-arm motion planning tasks in which the robot is holding an object with one hand in order to generate whole-body robot configurations suitable for grasping the object with both hands. In addition, we present two probabilistically complete RRT-based motion planning algorithms (J+-RRT and IK-RRT) that interleave the search for an IK solution with the search for a collision-free trajectory and the extension of these planners to solving re-grasping problems. The capabilities of combining IK methods and planners are shown both in simulation and on the humanoid robot ARMAR-III performing dual-arm tasks in a kitchen environment.

Keywords: Path Planning for Manipulators, Cooperative Manipulators, Path Planning for Multiple Mobile Robot Systems
Abstract: This paper presents a new method for planning motions of multi-arm systems in constrained workspaces, for which state-of-the-art planners behave poorly. The method is based on the decomposition of the system into parts. Compact roadmaps are first computed for each part, and then, a super-graph is constructed by the composition of elementary roadmaps. Results presented for a three-arm system and a model of the complex DLR’s Justin robot show a significant performance gain of such a two-stage roadmap construction method with respect to single-stage methods applied to the whole system.

Keywords: Visual Tracking, Localization, Computer Vision
Abstract: This paper describes a model-based probabilistic framework for tracking a fleet of laboratory-scale underwater vehicles using multiple fixed cameras. We model the target motion as a steered particle whose dynamics evolve on the special Euclidean group. We provide a likelihood function that extracts three-dimensional position and pose measurements from monocular images using projective geometry. The tracking algorithm uses particle filtering with selective resampling based on a threshold and nearest neighbor data association for multiple targets. We describe results obtained from two tracking experiments: first with one vehicle and a second experiment with two targets. The tracking algorithm for single target experiment is validated using data denial.

Keywords: Visual Tracking, Gesture, Posture, Social Spaces and Facial Expressions, Sensor Fusion
Abstract: Tracking people and objects is an enabling technology for many robotic applications. From human-robotinteraction to SLAM, robots must know what a scene contains and how it has changed, and is changing, before they can interact with their environment. In this paper, we focus on the tracking necessary to record the 3D position and pose of objects as they change in real time. We develop a tracking system that is capable of recovering object locations and angles at speeds in excess of 60 frames per second, making it possible to track people and objects undergoing rapid motion and acceleration. Results are demonstrated experimentally using real objects and people and compared against ground truth data.

Keywords: Visual Tracking, Manipulation and Compliant Assembly, Dexterous Manipulation
Abstract: Traditional industrial robots have been widely used in automotive manufacturing for nearly 30 years. However, there have been very few attempts to automate mobile robotic systems for final assembly operations, despite their potential for high flexibility and capability. This paper focuses on methods of tracking a dynamic moving vehicle that is similar to the vehicle body on a moving assembly line. We have investigated two tracking methods, one using a laser scanner and the other using a visual fiducial marker. We have also studied the tracking performance of a mobile base using the pure pursuit algorithm with low pass filtering. Experimental results are presented to illustrate the remaining main challenges in achieving robotic assembly on moving assembly lines.

Keywords: Visual Tracking, Visual Servoing, Computer Vision
Abstract: The problem considered here involves the design and application of a recursive algorithm to extract and predict the position of an object in a 3D environment from one feature correspondence from a monocular image sequence. Translational model involves an object moving in a parabolic path using projectile physics. A state-space model is constructed incorporating kinematic states, and recursive techniques are used to estimate the state vector as a function of time.

The measured data are the noisy image plane coordinates of object match taken from image in the sequence. Image plane noise levels are allowed. The problem is formulated as a tracking problem, which can use an arbitrary large number of images in a sequence. The recursive estimation is done using Recursive Least Squares (RLS).

Results on both synthetic and real imagery illustrate the performance of the estimator.

Keywords: Humanoid Robots, Cognitive Human-Robot Interaction, Legged Robots
Abstract: Programming a humanoid robot to perform an action that takes the robot's complex dynamics into account is a challenging problem. Traditional approaches typically require highly accurate prior knowledge of the robot's dynamics and environment in order to devise complex control algorithms for generating a stable dynamic motion. Training using human motion capture is an intuitive and flexible approach to programming a robot but directly applying motion capture data to a robot usually results in dynamically unstable motion. Optimization using high-dimensional motion capture data in the humanoid full-body joint-space is also typically intractable. In previous work, we proposed an approach that uses dimensionality reduction to achieve tractable imitation-based learning in humanoids without the need for a physics-based dynamics model. This work was based on a 3-D ``eigenpose'' representation. However, for some motion patterns, using only three dimensions for eigenposes is insufficient. In this paper, we propose a new method for motion optimization based on high-dimensional eigenpose data. A one-dimensional computationally efficient motion-phase optimization method is implemented along with a newly developed cylindrical coordinate transformation technique for hyperdimensional subspaces. This results in a fast learning algorithm and very accurate motion imitation. We demonstrate the new algorithm on a Fujitsu HOAP-2 humanoid robot model in a dynamic simulator and show that a dynamically stable sidestep motion can be successfully learned by imitating a human demonstrator.

Keywords: Humanoid Robots, Motion Control, Control Architectures and Programming
Abstract: This paper presents a control framework for humanoid robots that uses all joints simultaneously to track motion capture data and maintain balance. The controller comprises two main components: a balance controller and a tracking controller. The balance controller uses a regulator designed for a simplified humanoid model to obtain the desired input to keep balance based on the current state of the robot. The simplified model is chosen so that a regulator can be designed systematically using, for example, optimal control. An example of such controller is a linear quadratic regulator designed for an inverted pendulum model. The desired inputs are typically the center of pressure and/or torques of some representative joints. The tracking controller then computes the joint torques that minimize the difference from desired inputs as well as the error from desired joint accelerations to track the motion capture data, considering exact full-body dynamics. We demonstrate that the proposed controller effectively reproduces different styles of storytelling motion using dynamics simulation considering limitations in hardware.

Keywords: Humanoid Robots
Abstract: This work presents a methodology to generate dynamically stable whole-body motions for a humanoid robot, which are converted from human motion capture data. The methodology consists of the kinematic and dynamical mappings for human-likeness and stability, respectively. The kinematic mapping includes the scaling of human foot and Zero Moment Point (ZMP) trajectories considering the geometric differences between a humanoid robot and a human. It also provides the conversion of human upper body motions using the method in [1]. The dynamic mapping modifies the humanoid pelvis motion to ensure the movement stability of humanoid wholebody motions, which are converted from the kinematic mapping. In addition, we propose a simplified human model to obtain a human ZMP trajectory, which is used as a reference ZMP trajectory for the humanoid robot to imitate during the kinematic mapping. A human whole-body dancing motion is converted by the methodology and performed by a humanoid robot with on-line balancing controllers.

Keywords: Humanoid Robots, Gesture, Posture, Social Spaces and Facial Expressions, Biologically-Inspired Robots
Abstract: This paper models recent data in the field of postural coordination showing the existence of self-organized postural states, and transition between them, underlying suprapostural tracking movements. The proposed closed-loop controller captures the complex postural behaviors observed in humans and can be used to implement efficient and simple balance control principles in humanoids.

Keywords: Humanoid Robots, Force and Tactile Sensing, Motion Control
Abstract: To help with care work and rescue operations, it is necessary for humanoid robots to have the ability to transport humans steadily and gently.In this research we consider ``piggyback'' motions for transporting humans.Most people can perform this motion, allowing us to measure and analyze piggyback motions of human subjects using tactile sensing and whole body movements to design whole body contact control. One interesting result of this investigation is that frictional forces are skillfully controlled by the carrier. In the first experiment, we study a ``knack'' that allows the carrier to reposition the rider. The knacks are follows: using the hip to launch the rider up, bending forward to catch the rider. In the second experiment we verify the effectiveness of the knacks in achieving the repositioning result. We also studied the principle of the repositioning motion, and found that it is similar in many ways to a jumping motion. Then we confirmed the validity of our modeling assumptions and knacks using a dynamical simulator.

Keywords: Social Human-Robot Interaction, Learning and Adaptive Systems, Gesture, Posture, Social Spaces and Facial Expressions
Abstract: Human-Robot Interaction using free hand gestures is gaining more importance as more untrained humans are operating robots in home and office environments. The robot needs to solve three problems to be operated by free hand gestures: gesture (command) detection, action generation (related to the domain of the task) and association between gestures and actions. In this paper we propose a novel technique that allows the robot to solve these three problems together learning the action space, the command space, and their relations by just watching another robot operated by a human operator. The main technical contribution of this paper is the introduction of a novel algorithm that allows the robot to segment and discover patterns in its perceived signals without any prior knowledge of the number of different patterns, their occurrences or lengths. The second contribution is using a Ganger-Causality based test to limit the search space for the delay between actions and commands utilizing their relations and taking into account the autonomy level of the robot. The paper also presents a feasibility study in which the learning robot was able to predict actor’s behavior with 95.2% accuracy after monitoring a single interaction between a novice operator and a WOZ operated robot representing the actor.

Keywords: Cognitive Human-Robot Interaction, Evolutionary Robotics, Learning and Adaptive Systems
Abstract: This paper describes an novel approach towards linguistic processing for robots through integration of a motion language module and a natural language module. The motion language module represents association between symbolized motion patterns and words. The natural language module models sentences. The motion language module and the natural language module are graphically integrated. The integration allows robots not only to interpret observed motion as a sentence but also to generate motion with a sentence. This paper proposes incremental learning algorithm of association between symbolized motion patterns and words. The incremental learning is required for robot to autonomously develop the linguistic skill. The algorithm can be derived from optimization of the motion language module under stochastic constraints such that the associative probability of a new training pair composed of symbolized motion pattern and sentence becomes larger. Test of interpreting observed motion as sentences demonstrates the validity of the proposed incremental learning algorithm.

Keywords: Cognitive Human-Robot Interaction, Social Human-Robot Interaction
Abstract: In a Robot Learning from Demonstration framework involving environments with many objects, one of the key problems is to decide which objects are relevant to a given task. In this paper, we analyze this problem and propose a biologically-inspired computational model that enables the robot to focus on the task-relevant objects. To filter out incompatible task models, we compute a Task Relevance Value (TRV) for each object, which shows a human demonstrator’s implicit indication of the relevance to the task. By combining an intentional action representation with ‘motionese’ [2], our model exhibits recognition capabilities compatible with the way that humans demonstrate. We evaluate the system on demonstrations from five different human subjects, showing its ability to correctly focus on the appropriate objects in these demonstrations.

Keywords: Cognitive Human-Robot Interaction, Biologically-Inspired Robots, Learning and Adaptive Systems
Abstract: Many kinds of sound source localization systems have been developed for detecting a direction of sound source. They are commonly using time delay of arrival (TDOA) or interaural time difference (ITD) algorithm for sound source localization, especially the ITD is the difference in arrival time of a sound between two ears. It is largely changed depending on frequency components of sound even though the sound source is located in the same place. In this paper we propose a binaural sound localization system using sparse coding and self-organizing map (SOM). The sparse coding is used for decomposing a given sound into time, frequency and magnitude. Moreover we estimate the azimuth angle through the SOM. This system is installed in a robot that has two ears, head and body. We use PeopleBot as a body of the robot.

Keywords: Social Human-Robot Interaction, Personal Robots, Humanoid Robots
Abstract: Persuasive Robotics is the study of persuasion as it applies to human-robot interaction (HRI). Persuasion can be generally defined as an attempt to change another's beliefs or behavior. The act of influencing others is fundamental to nearly every type of social interaction. Any agent desiring to seamlessly operate in a social manner will need to incorporate this type of core human behavior. As in human interaction, myriad aspects of a humanoid robot's appearance and behavior can significantly alter its persuasiveness -- this work will focus on one particular factor: gender. In the current study, run at the Museum of Science in Boston, subjects interacted with a humanoid robot whose gender was varied. After a short interaction and persuasive appeal, subjects responded to a donation request made by the robot, and subsequently completed a post-study questionnaire. Findings showed that men were more likely to donate money to the female robot, while women showed little preference. Subjects also tended to rate the robot of the opposite sex as more credible, trustworthy, and engaging. In the case of trust and engagement the effect was much stronger between male subjects and the female robot. These results demonstrate the importance of considering robot and human gender in the design of HRI.

Keywords: Medical Robots and Systems, Motion Control, Wheeled Robots
Abstract: This paper discusses the tracking algorithms and approach used to control the Tracking Fluoroscope System. It is a mobile platform equipped with an on-board fluoroscope system to perform real-time imaging of human joints in motion: ankles, knees and hips. In order to record the natural and uninterrupted joint motion, the person has to be able to walk freely while being followed by the robot. It requires independent tracking of the position and orientation of the body with respect to the platform as well as joints position with respect to the trunk of the body. This paper investigates the problem of tracking position and orientation of a walking person with respect to the following robotic platform

Keywords: Force and Tactile Sensing, Rehabilitation Robotics, Mechanism Design
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Keywords: Medical Robots and Systems, Calibration and Identification, Force Control
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Keywords: Medical Robots and Systems, Multifingered Hands, Grasping
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Keywords: Medical Robots and Systems, Force Control
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Keywords: Learning and Adaptive Systems, Humanoid Robots, Biologically-Inspired Robots
Abstract: For a complex autonomous robotic system such as a humanoid robot, motor-babbling-based sensorimotor learning is considered an effective method to develop an internal model of the self-body and the environment autonomously. In this paper, we propose a method of sensorimotor learning which explores the learning domain actively. The proposed model is characterized by a function we call the `` confidence'', and is a measure of the reliability of state control. The confidence for the state can be a good measure to bias the exploration strategy of data sampling, and to direct its attention to areas of learning interest. We consider the confidence function to be a first step toward an active behavior design for autonomous environment adaptation. The approach was experimentally validated using the humanoid robot James.

Keywords: Learning and Adaptive Systems, Autonomous Agents, Agent-Based Systems
Abstract: Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle real-world sequential decision processes but require a known model to be solved by most approaches. However, mainstream POMDP research focuses on the discrete case and this complicates its application to most realistic problems that are naturally modeled using continuous state spaces. In this paper, we consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are unknown. We advocate the use of Gaussian Process Dynamical Models (GPDMs) so that we can learn the model through experience with the environment. Our results on the blimp problem show that the approach can learn good models of the sensors and actuators in order to maximize long-term rewards.

Keywords: Learning and Adaptive Systems, Grasping
Abstract: Abstract--- When children learn to grasp a new object, they often know several possible grasping points from observing a parent's demonstration and subsequently learn better grasps by trial and error. From a machine learning point of view, this process is an active learning approach. In this paper, we present a new robot learning framework for reproducing this ability in robot grasping. For doing so, we chose a straightforward approach: first, the robot observes a few good grasps by demonstration and learns a value function for these grasps using Gaussian process regression. Subsequently, it chooses grasps which are optimal with respect to this value function using a mean-shift optimization approach, and tries them out on the real system. Upon every completed trial, the value function is updated, and in the following trials it is more likely to choose even better grasping points. This method exhibits fast learning due to the data-efficiency of Gaussian process regression framework and the fact that the mean-shift method provides maxima of this cost function. Experiments were repeatedly carried out successfully on a real robot system. After less than sixty trials, our system has adapted its grasping policy to consistently exhibit successful grasps.

Keywords: Learning and Adaptive Systems, Neural and Fuzzy Control
Abstract: Neurobiology studies showed that the role of the Anterior Cingulate Cortex of the brain is primarily responsible for avoiding repeated mistakes. According to vigilance threshold, which denotes the tolerance to risks, we can differentiate between a learning mechanism that takes risks, and one that averts risks. The tolerance to risk plays an important role in such learning mechanism. Results have shown the differences in learning capacity between risk-taking and risk avert behaviors. In this paper, we propose a learning mechanism that is able to learn from negative and positive feedback. It is composed of two phases, evaluation and decision-making phase. In the evaluation phase, we use a Kohonen Self Organizing Map technique to represent success and failure. Decision-making is based on an early warning mechanism that enables to avoid repeating past mistakes. Our approach is presented with an implementation on a simulated planar biped robot, controlled by a reflexive low-level neural controller. The learning system adapts the dynamics and range of a hip sensor neuron of the controller in order for the robot to walk on flat or sloped terrain. Results show that success and failure maps can learn better with a threshold that is more tolerant to risk. This gives rise to robustness to the controller even in the presence of slope variations.

Keywords: Learning and Adaptive Systems, Autonomous Agents, Mechanism Design
Abstract: In this paper, we propose the design of a robot with a snake-like body based on an environment. We explore the abstraction of state-action spaces for reinforcement learning. Additionally, we discuss the versatility of the proposed mechanism by showing that different tasks can be completed by simply changing the reward of the reinforcement learning. Finally, we mention the importance of a body design based on an environment by considering the concept of ecological niches.

Keywords: Medical Robots and Systems, Computer Vision
Abstract: For robotic assisted minimally invasive surgery, recovering the 3D soft-tissue shape and morphology in vivo is important for providing image-guidance, motion compensation and applying dynamic active constraints. In this paper, we propose a practical method for calibrating the illumination source position in monocular and stereoscopic laparoscopes. The method relies on using the geometric constraints from specular reflections obtained during the laparoscope camera calibration process. By estimating the light source position, the method forgoes the common assumption of coincidence with the camera centre and can be used to obtain constraints on the normal of the surface geometry during surgery from specularities. We demonstrate the effectiveness of the proposed approach with numerical simulations and by qualitative analysis of real stereo-laparoscopic calibrations.

Keywords: Force Control, Medical Robots and Systems
Abstract: This paper presents a predictive force control approach to compensate for the physiological motion induced by both respiratory and heart beating motions during cardiac surgery. It focuses on the design and implementation of the control algorithm in the context of robotized minimally invasive surgery. The controller is based on a linear predictive control loop using the force information applied on the heart by the instrument. Experimental evaluation highlights the performance of the algorithm for compensating 3D physiological motion.

Keywords: Force and Tactile Sensing
Abstract: IIn this paper, the design of a novel MRI-compatible torque sensor is proposed. The sensor is based on an optical measurement, with a particular architecture to provide a very low cross-sensitivity. Its structure allows to simultaneously tune the sensor stiffness and the measurement amplitude of the optical sensor. To do so, kinematic singularities of parallel structures are used as well as the principles of dissociated metrology structure. The design of the sensor is first introduced by a kinematic analysis, before detailing its behavior using Finite Element Analysis. A prototype is finally introduced with first experimental results.

Keywords: Force and Tactile Sensing, Haptics and Haptic Interfaces, Medical Robots and Systems
Abstract: This paper presents a novel air-cushion tactile sensor for Minimally Invasive Surgery that is fully MRI (Magnetic Resonance Imaging) compatible. The proposed sensor is designed to detect tissue abnormalities within soft tissue surfaces. This is achieved by rolling over soft tissue in a virtually frictionless manner due to the design of the sensor in which the sensing element, a sphere, rests on a cushion of air. This design allows for rapid acquisition of tactile and mechanical properties of large areas of soft tissue. Laboratory experiments are carried out to show its feasibility as a tactile sensor for MIS and its behaviour under loading. The outcomes of the experiments illustrate the sensor’s capability and potential as a tactile sensor for MIS. These results are discussed and future work is outlined.

Keywords: Force Control, Medical Robots and Systems
Abstract: This paper is focused on the motion control problem for a laparoscopic surgery robot assistant with an actuated wrist. These assistants may apply non-desired efforts to the patient abdomen. Therefore, this article proposes a control methodology based on three feedback levels, which have been defined as layers. These layers control different aspects of the endoscope movement. A low level assures the dynamic of the robot assistant is performed accordingly. The mid level emulates a passive wrist behavior to avoid any efforts over the abdomen. An external high level deals with the global movement planning. This architecture also makes easier to analyze the stability of the whole system. Finally, a real in-vitro experiment has been implemented with an industrial robot in order to contrast the validity of this article procedure.

Keywords: Biologically-Inspired Robots, Kinematics, Search and Rescue Robots
Abstract: This paper introduces a method for modeling a continuum robot as a rod in 3-D space. The cosserat rod theory is applied to a continuum robot. With this theory, the rod can be solved using force-torque balance equations obtained from a simple free body diagram that represents the continuum robot.

Keywords: Biologically-Inspired Robots, Legged Robots
Abstract: The ability to traverse a wide variety of terrains while walking is basically a requirement for performing useful tasks in our human centric world.

In this article, we propose a bio-inspired robotic controller able to generate locomotion and to easily switch among different type of gaits. In order to improve the robot stability and response while locomoting, we adjust both the duty factor and the interlimb phase relationships, according to the velocities.

We extend previous work, by applying nonlinear oscillators to generate the rhythmic locomotor movements for a quadruped robot, similarly to the biological counterparts. The generated trajectories are modulated by a drive signal, that modifies the oscillator frequency, amplitude and the coupling parameters among the oscillators, proportionally to the drive signal strength. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori.

The implementation of the central pattern generator network and the activity modulation layer is shown in simulation and in an AIBO robot.

Keywords: Legged Robots, Biologically-Inspired Robots
Abstract: Improvement of the adaptability of a quadruped robot in rough terrain is studied in this paper. First, the position and posture of the body of the robot are adjusted to maximize the number of choices for foot placement of the next swing leg. The more choices the robot has to select the next suitable foothold, the better it will be to cope with rough terrain. Second, an effective foothold search algorithm is developed. The foothold search algorithm not only tries to find a valid foothold but also tries to maintain high adaptability of the robot. For implementing the algorithm, some new concepts such as potential swing direction, complementary kinematic margin and elliptical set of candidate footholds are also proposed. The effectiveness of this procedure in improving the adaptability of a quadruped robot moving in challenging terrain is verified in both simulation and experiment.

Keywords: Biologically-Inspired Robots, Neurorobotics, Voice, Speech Synthesis and Recognition
Abstract: In this particular paper, we build a novel active vision system which detects weak signals by generating tremor actively. Proposed active vision system consists of a noise generator and a neural system. As a noise generator, we use motors with a decentered weight. And as a neural system in order to detect visual signals, we use ensemble of FitzHugh-Nagumo neurons. We first show that our robotic platform can generate several kinds of tremors; tremor around 40 Hz, 50Hz, and tremor which does not involve specific peak in its power spectrum. And, in order to evaluate the effect of tremor, we prepare clear-films as visual stimuli which move aperiodically in a dark environment. We show that as a result of sensory noise induced by tremor, and as a result of stochastic resonance, neural system successfully detects movements of clear films.

Keywords: Biologically-Inspired Robots, Legged Robots, Micro/Nano Robots
Abstract: DASH is a small, lightweight, power autonomous robot capable of running at speeds up to 15 body lengths per second (see video). Drawing inspiration from biomechanics, DASH has a sprawled posture and uses an alternating tripod gait to achieve dynamic open-loop horizontal locomotion. The kinematic design which uses only a single drive motor and allows for a high power density is presented. The design is implemented using a scaled Smart Composite Manufacturing (SCM) process. Evidence is given that DASH runs with a gait that can be characterized using the spring-loaded inverted pendulum (SLIP) model. In addition to being fast, DASH is also well suited to surviving falls from large heights, due to the uniquely compliant nature of its structure.

Keywords: Computer Vision, Visual Tracking, Recognition
Abstract: The problem of accurate 6-DoF pose estimation of 3D objects based on their shape has so far been solved only for specific object geometries. Edge-based recognition and tracking methods rely on the extraction of straight line segments or other primitives. Straight-forward extensions of 2D approaches are potentially more general, but assume a limited range of possible view angles. The general problem is that a 3D object can potentially produce completely different 2D projections depending on the view angle. One way to tackle this problem is to use canonical views. However, accurate shape-based 6-DoF pose estimation requires more information than matching of canonical views can provide. In this paper, we present a novel approach to 6-DoF pose estimation of single-colored objects based on their shape. Our approach combines stereo triangulation with matching against a high-resolution view set of the object, each view having associated orientation information. The errors that arise from separating the position and orientation computation in first place are corrected by a subsequent correction procedure based on online 3D model projection. The proposed approach can estimate the pose of a single object within 20 ms using conventional hardware.

Keywords: Computer Vision, Localization, Visual Tracking
Abstract: Accurate online localization is crucial for mobile robotics. In this paper, we describe a real-time image-based localization technique, which is based on a single calibrated camera. This can be supported by a second camera to improve accuracy and to provide the correct translational scale. Our goal is a robust and unbiased pose estimation in highly dynamic scenes on resource-limited systems. The presented approach is characterized through significantly improved robustness of the pose estimation, a novel approach for stereo subpixel accurate landmark initialization, and the speed-up of conventional tracking routines to achieve online capability. Although the algorithm is designed for accurate, online short-range egomotion estimation in hand-held scanning devices, it can be used for any mobile robot application as shown in this paper. Various tests and experimental results with a mobile platform and a hand-held 3D modeler are presented and discussed.

Keywords: Navigation, Computer Vision, Intelligent Vehicles
Abstract: In this paper we propose a new algorithm for relative pose estimation between two images based on a new decomposition for an homography matrix faster than the classical solutions.We introduce in our method approximate information about the planes in the reference images but this additional information allows the decomposition to avoid the multiplicity of solutions. An exhaustive analysis of the error propagation through the method is provided. The new decomposition can be used for visual navigation of robots moving on a planar surface. The approach is based in the well known teaching-bydoing scheme with the route defined by a set of images. The parameters of the planes can be computed automatically from the reference images before the navigation. The contributions are the easy method to extract the parameters of all the planes and the use of this information in navigation tasks using a fast homography decomposition. The experimental results show the performance of the proposal.

Keywords: Computer Vision, Control Architectures and Programming
Abstract: Finding objects and tracking their poses are essential functions for service robots, in order to manipulate objects and interact with humans. We present an approach for object detection and 3D pose estimation for autonomous mobile robots, that is suitable for general uses in a modularized robot control system. Our apprach extracts local features from the input images, searches for the reference pattern, and then produces the 3D pose in camera coordinate system, using only a single reference image and the 6-DOF pose in it. We have created an RT(Robot Technology) component that can be used in any RT-based system, and developed an algorithm that can extend the range of detection and produce robust pose estimation. For evaluation, we have integrated our vision component in an autonomous robot system with a search-and-grasp task, and tested it with several objects that are found in ordinary domestic environment. We present the details of our approach, the design of our modular component design, and the results of the experiments in this paper.

Keywords: Localization, Medical Robots and Systems, Human Performance Augmentation
Abstract: This paper presents an indoor localization system for the visually impaired. The basis of our system is an Extended Kalman Filter (EKF) for six degree-of-freedom (d.o.f.) position and orientation (pose) estimation. The sensing platform consists of an Inertial Measurement Unit (IMU) and a 2D laser scanner. The IMU measurements are integrated to obtain pose estimates which are subsequently corrected using line-to-plane correspondences between linear segments in the laser-scan data and known 3D structural planes of the building. Furthermore, we utilize Lie derivatives to show that the system is observable when at least three planes are detected by the laser scanner. Experimental results are presented that demonstrate the reliability of the proposed method for accurate and real-time indoor localization.

Keywords: Recognition, Personal Robots
Abstract: This paper proposes a sound identification method for a mobile robot in home and office environment. We propose a simple sound database called Pitch-Cluster-Maps(PCMs) based on Vector Quantization approach. Binarized frequency spectrum is used for PCMs codebook generation. It can describe a variety of sound sources, not only voice, from short term sound input. The proposed PCMs sound identification requires several tens(msec) of sound input, and is suitable for a mobile robot application which condition is dynamically changing. We implemented the proposed method on our mobile robot audition system equipped with a 32ch microphone array. Robot noise reduction using proposed PCMs recognition is applied to each input signal of a microphone array. The performance of daily sound recognition for separated sound sources from robot in motion is evaluated.

Keywords: Voice, Speech Synthesis and Recognition, Social Human-Robot Interaction, Humanoid Robots
Abstract: A humanoid robot must recognize a target speech signal while people around the robot chat with them in realworld. To recognize the target speech signal, robot has to separate the target speech signal among other speech signals and recognize the separated speech signal. As separated signal includes distortion, automatic speech recognition (ASR) performance degrades. To avoid the degradation, we trained an acoustic model from non-clean speech signals to adapt acoustic feature of distorted signal and adding white noise to separated speech signal before extracting acoustic feature. The issues are (1) To determine optimal noise level to add the training speech signals, and (2) To determine optimal noise level to add the separated signal.

In this paper, we investigate how much noises should be added to clean speech data for training and how speech recognition performance improves for different positions of three talkers with soft masking. Experimental results show that the best performance is obtained by adding white noises of 30 dB. The ASR with the acoustic model outperforms with ASR with the clean acoustic model by 4 points.

Keywords: Voice, Speech Synthesis and Recognition, Humanoid Robots, Localization
Abstract: A new noise reduction method suitable for autonomous mobile robots was proposed and applied to preprocessing of a hands-free spoken dialogue system. When a robot talks with a conversational partner in real environments, not only speech utterances by the partner but also various types of noise, such as directional noise, diffuse noise, and noise from the robot, are observed at microphones. We attempted to remove these types of noise simultaneously with small and light-weighted devices and low-computational-cost algorithms. We assumed that the conversational partner of the robot was in front of the robot. In this case, the aim of the proposed method is extracting speech signals coming from the frontal direction of the robot. The proposed noise reduction system was evaluated in the presence of various types of noise: the number of word errors was reduced by 69 % as compared to the conventional methods. The proposed robot auditory system can also cope with the case in which a conversational partner (i.e., a sound source) moves from the front of the robot: the sound source was localized by face detection and tracking using facial images obtained from a camera mounted on an eye of the robot. As a result, various types of noise could be reduced in real time, irrespective of the sound source positions, by combining speech information with image information.

Keywords: Biologically-Inspired Robots, Autonomous Agents
Abstract: First task robots have to realise is sensing and acting in the environment. Can a robot learn the way it is able to sense and act in the world without any hardwired notions? Is it able to learn it from the only data he has access to, that is high-dimension sensory inputs and motor outputs? This paper presents experimental results obtained on a simulated human listener using a bio-inspired model of the cochlea and real records from human related transfer functions (HRTF). These results show that a naive system that interacts with its environment without knowing the laws governing these interactions can discover information about dimensionality of space. Moreover, the laws determining the sensations of the system as a function of the state of the system and the environment, called the ``sensorimotor law'', are not simplified as usually in simulations. They are bio-realistic as they are determined by the HRTF recorded on human beings.

Keywords: Voice, Speech Synthesis and Recognition
Abstract: When adults talk to infants they do that in a different way compared to how they communicate with other adults. This kind of Infant Directed Speech (IDS) typically highlights target words using focal stress and utterance final position. Also, speech directed to infants often refers to objects, people and events in the world surrounding the infant. Because of this, the sound sequences the infant hears are very likely to co-occur with actual objects or events in the infant's visual field. In this work we present a model that is able to learn word-like structures from multimodal information sources without any pre-programmed linguistic knowlege, by taking advantage of the characteristics of IDS. The model is implemented on a humanoid robot platform and is able to extract word-like patterns and associating these to objects in the visual surrounding.

Keywords: Micro/Nano Robots, Biologically-Inspired Robots, Mechanism Design
Abstract: This paper continues the exploration of the design space for an insect-sized autonomous flapping-wing MAV with the goal of stable hovering. Previous work has focused on the use of a large primary power actuator to generate flapping motion and smaller “control” actuators to asymmetrically alter wing kinematics. Here a new iteration of this concept is presented, merging the two actuator types to create a “hybrid” power-control actuator. Kinematic and dynamic models for wing motion are presented, and the predictions of these models are compared to experimental results from a prototype design. Controllable asymmetry in wing kinematics can be mapped into controllable body torques via an aerodynamic model, and this information can be used for the generation of control laws for stable hover and eventually highly agile aerial vehicles.

Keywords: Cellular and Modular Robots, Micro/Nano Robots, Mechanism Design
Abstract: As the size of the modules in a self-reconfiguring modular robotic system shrinks and the number of modules increases, the flexibility of the system as a whole increases. In this paper, we describe the manufacturing methods and mechanisms for a 1 millimeter diameter module which can be manufactured en masse. The module is the first step towards realizing the basic unit of claytronics, a modular robotic system designed to scale to millions of units.

Keywords: Micro/Nano Robots, Mechanism Design, Biologically-Inspired Robots
Abstract: We present an approach to quantifying the off-axis stiffness properties of parallel compliant mechanisms used in the design of mobile millirobots. By transforming the stiffness of individual flexure elements and rigid links comprising a compliant mechanism into a global coordinate system, we enable the formulation of an equivalent mechanism stiffness. Using that stiffness in concert with an energy-based performance metric, we predict the performance of a compliant mechanism subjected to a prescribed set of forces in the global coordinate system. We analyze a flexure-based Sarrus linkage and use the performance metric to improve the design by adding topological redundancy. Finally, our approach is experimentally validated by constructing and testing SCM Sarrus linkages in a variety of geometries and topologies and demonstrating agreement between the model and our experiments.

Keywords: Micro/Nano Robots
Abstract: Photo-patternable adhesives and silicones are introduced for use in centimeter-scale robotics. Traditional approaches to making robots at this size scale require the use of expensive start-up equipment and/or precise machining, and generally yield fragile and costly robots in small numbers.The multi-material milli-robot prototyping process uses Loctite® polymer products and photolithography to rapidly fabricate robust, inexpensive, and compliant robots only centimeters in size. In this paper, the process flow is described and characterized with minimum feature sizes of 0.25 mm in polymer layers 0.18 mm thick. Both commercial and ink-jet printed masks are used for the photolithography steps. Finally, a functional inchworm robot and a small gripper have been designed and demonstrated with Nitinol shape memory alloy(SMA) used for actuation. The gripper is 1.2 g and costs 3.21 in small numbers while the inchworm robot is 7.4 g and costs 7.76 in small numbers. Building a functional robot from a computer design takes less than 1 hour.

Keywords: Human Performance Augmentation, Visual Tracking, Virtual Reality and Interfaces
Abstract: This paper presents a human-robot interface with perceptual docking to allow for the control of multiple microbots. The aim is to demonstrate that real-time eye tracking can be used for empowering robots with human vision by using knowledge acquired in situ. Several micro-robots can be directly controlled through a combination of manual and eye control. The novel control environment is demonstrated on a virtual biopsy of gastric lesion through an endoluminal approach. Twenty-one subjects were recruited to test the control environment. Statistical analysis was conducted on the completion time of the task using the keyboard control and the proposed eye tracking framework. System integration with the concept of perceptual docking framework demonstrated statistically significant improvement of task execution.

Keywords: Search and Rescue Robots, Field Robots, Robotics in Hazardous Fields
Abstract: Robot technology is emerging for applications in disaster prevention with devices such as fire-fighting robots, rescue robots, and surveillance robots. In this paper, we suggest an portable fire evacuation guide robot system that can be thrown into a fire site to gather environmental information, search displaced people, and evacuate them from the fire site. This spool-like small and light mobile robot can be easily carried and remotely controlled by means of a laptop-sized tele-operator. It contains the following functional units: a camera to capture the fire site; sensors to gather temperature data, CO gas, and O2 concentrations; and a microphone with speaker for emergency voice communications between firefighter and victims. The robot’s design gives its high-temperature protection, excellent waterproofing, and high impact resistance. Laboratory tests were performed for evaluating the performance of the proposed evacuation guide robot system.

Keywords: Search and Rescue Robots, Autonomous Agents, Cooperating Robots
Abstract: Fire brigades and special agencies are often demanded to operate for search and aid of human lives in extremely dangerous scenarios. It is very important to first verify the safety of the environment and to obtain remotely a clear image of the scenario inside buildings or underground spaces. Several studies have been addressing the possibility of using robotic tools to carry out safe operations.

This contribution presents the development of the HELIOS team, consisting of five tracked robots for Urban Search And Rescue. Two units are equipped with manipulators for the accomplishment of particular tasks, such as the handling of objects and opening doors; the other three units, equipped with cameras and laser range finders, are utilized to create virtual 3D maps of the explored environment. The three units can move autonomously while collecting the data by using a collaborative positioning system (CPS).

After an overview on the specifications of the team of robots and with respect to previous publications, detailed information about the improvements of the robot mechanical design and control systems are introduced. Tests of the CPS system and HELIOS IX vehicle together with a typical mission experiment are presented and discussed.

Keywords: Search and Rescue Robots, Mechanism Design, Field Robots
Abstract: In this paper, a tetrahedral mobile robot with central axis for transformation to the flat vehicle is presented. The throwable robot with the function of going into narrow spaces when its in the flat-vehicle mode is explained in detail. A prototype has been developed to illustrate the concept. Motion experiments confirm the novel properties of this mechanism: mode changing function and omnidirectional motion. Basic Motion experiments, with a test vehicle are also presented.

Keywords: Search and Rescue Robots, Robotics in Hazardous Fields, Autonomous Agents
Abstract: In the current research we consider the scenario of post disaster rescue operations using multiple robots inside damaged buildings where the damage is not very extreme. The objective the of the work is to develop systems to support efficient rescue missions involving creation and exchange of environment maps enriched with information important to rescue operations, among multiple robots and rescue workers. In current days many research institutes are developing robots with widely different types and capabilities to support rescue operations. In rescue missions involving multiple robots it is essential to have sharable map information for efficient search and navigation irrespective of the differences in the structures and capabilities of the participating robots. In this paper we address the above issue by proposing a map description which combines the geographical data as well as the information about robot behaviors called ”Behavioral Trace Map”. We describe the algorithm for generation of such maps and we present experimental results using rescue robots developed in our laboratory.

Keywords: Search and Rescue Robots, Range Sensing, Autonomous Agents
Abstract: For tracked vehicles moving over rough terrain, it is important to avoid rollovers and rapid motion. To realize smooth locomotion on rough terrain, some tracked vehicles are equipped with “active flippers.” Such flippers increase the traversability and stability of tracked vehicles. However, their control increases the operator workload, especially in the case of teleoperation.

To eliminate this problem, we have developed an autonomous controller for generating terrain-reflective motions of flippers. Terrain information is obtained using laser range sensors that are located at both sides of our tracked vehicle testbed. Using this system, operators only have to specify a direction to the robot, following which the robot traverses rough terrain using autonomous flipper motions. In this paper, we introduce a strategy and an algorithm for the controller for active flippers and validate the reliability of the system through experimental results on rough terrain.

Keywords: Networked Teleoperation, Networked Robots, Motion Control
Abstract: We applied partial feedback linearization to the unicycle model to stabilize part of the state at a desired position on the plane and extend it to design formation control for teleoperation. Further, using output synchronization results we derive a Single Master Multiple Slave bilateral teleoperation system robust to constant unknown, possible different time delays between master and formation and among mobile robots and formation. We show our simulation's results to illustrate the performance of the derived control law.

Keywords: Networked Robots, Sensor Networks, Ubiquitous Robotics
Abstract: This paper introduces a testbed for sensor and robot network systems, currently composed of 10 cameras and 5 mobile wheeled robots equipped with several sensors for self-localization, obstacle avoidance and vision cameras, and wireless communications. The testbed includes a service-oriented middleware to enable fast prototyping and implementation of algorithms previously tested in simulation, as well as to simplify integration of subsystems developed by different partners. We survey an integrated approach to human-robot interaction that has been developed supported by the testbed under an European research project. The application integrates innovative methods and algorithms for people tracking and waving detection, cooperative perception among static and mobile cameras to improve people tracking accuracy, as well as decision-theoretical approaches to sensor selection and task allocation within the sensor network.

Keywords: Networked Robots, Distributed Robot Systems, Localization
Abstract: We study radio signal propagation in indoor environments using low-power devices leveraging the Zigbee and Bluetooth specifications. We present results from experiments where two robots equipped with radio signal devices and enabled to control and localize autonomously in an indoor hallway and laboratory environment densely sample RSSI at various times over several days. We show that simulated RSSI measurements using existing radio signal models and experimentally gathered RSSI measurements match closely, suggesting that for robotics applications requiring predicted RSSI, low-power radio signal devices are a well-posed sensing modality.

Keywords: Networked Robots, Service Robots, Path Planning for Multiple Mobile Robot Systems
Abstract: In previous work we presented a multi-robot strategy for routing missions in large scenarios where network connectivity must be explicitly preserved. This strategy is founded on the traversal of path trees in such a way that connectivity to a static control center is always maintained, while ensuring that any target that is reachable by a chain consisting of all robots is eventually visited. In this work we improve the strategy performance by extending its sequential one-task-at-a-time execution approach with concurrent execution of tasks. We demonstrate that the general problem is NP-hard and offer several heuristic approaches to tackle it. We study the improvements that these heuristics can offer in regard to several important variables like network range and clustering of targets, and finally compare their performance over the optimal solutions for small problem instances. In summary, we offer a complete characterization of the new concurrent capabilities of the ConnectTree strategy.

Keywords: Networked Robots, Social Human-Robot Interaction, Service Robots
Abstract: This paper reports the challenges of developing multiple social robots that operate in a shopping mall. We developed a networked robot system that coordinates multiple social robots and sensors to provide efficient service to customers. It directs the tasks of robots based on their positions and people' s walking behavior, manages the paths of robots, and coordinates the conversation-performance between two robots. Laser range finders were distributed in the environment to estimate people' s positions. The system estimates such human walking behaviors as "stopping" or "idle walking" to direct robots to provide appropriate tasks to appropriate people. Each robot interacts with people to provide recommendation information and route information about shops. The system sometimes simultaneously uses two robots to lead people from one place to another. The field trial, which was conducted in a shopping mall where four robots interacted with 414 people, revealed the effectiveness of the network robot system for guiding people around a shopping mall as well as increasing their interest.

Keywords: Aerial Robotics, Search and Rescue Robots, Biologically-Inspired Robots
Abstract: Flapping-wing air vehicles can improve efficiency by running at resonance to reduce inertial costs of accelerating and decelerating the wings. For battery-powered, DC motor-driven systems with gears and cranks, the drive torque and velocity is a complicated function of battery voltage. Hence, resonant behavior is not as well defined as for flapping-wing systems with elastic actuators. In this paper, we analyze a resonant drive to reduce average battery power consumption for DC motor-driven flapping-wing robots. We derive a nondimensionalized analysis of the generic class of a motor-driven slider crank, considering motor and battery resistance. This analysis is used to demonstrate the benefits of efficient resonant drive on a 5.8g flapping-wing robot and experiments showed a 30% average power reduction by integrating a tuned compliant element.

Keywords: Aerial Robotics, Mechanism Design, Search and Rescue Robots
Abstract: This paper discusses the improvement of the simulation model and the development of the new mechanism for flight control of a flying robot with the cyclogyro wing. In past study, we focused high maneuverability of the flying robots with the cyclogyro wing, whose rotor had rotation along horizontal axis, and developed some prototypes. The simulation model was also constructed based on the pressure of air. However the Reynolds number was not considered in the constructed simulation model. As a results, the model's accuracy was not enough. On the other hand, the control mechanism for the flight of cyclogyro wing is not yet developed. In this paper, the simulation model is improved by considering the cyclogyro's Reynolds number. The utility of the improved simulation model is verified by comparing simulation results with experimental results. Moreover the new mechanism is suggested for the flight control by controlling the generated force direction. The prototype of the new mechanism is developed and validated by the experiment.

Keywords: Aerial Robotics, Sensor Fusion, Dynamics
Abstract: This paper presents a nonlinear observer algorithm for attitude estimation that improves the quality of measures obtained by using low-cost inertial measurements (IMU). It is based on sliding mode observer that provides both the estimates of the gyro-bias and the actual attitude of the rigid body. The algorithm was developed in order to address the well-known problem of the weak dynamics of the tilt sensors and magnetometers, which can be modeled by low pass filters, and of the measurement bias of the gyros. In its design the observer uses the real measurements given by the low-cost attitude sensors (inclinometers and magnetometers) and the gyros, the filters modeling the sensors and the kinematics equation of the rigid body. The asymptotic convergence of the estimation of the attitude and bias-gyros was proven using Lyapunov stability method. The effectiveness of the algorithm has been shown from experimental tests using a rotary platform equipped with several sensors with axes of rotation coincide with orientation of the rigid body. Also, tests for comparison with a linear complementary filter are given.

Keywords: Aerial Robotics, Motion Control
Abstract: Most autopilots of existing Miniature Unmanned Air Vehicles (MUAVs) rely on control architectures that typically use a large number of sensors (gyros, accelerometers, magnetometers, GPS) and a computationally demanding estimation of flight states. As a consequence, they tend to be complex, require a significant amount of processing power and are usually expensive. Many research projects that aim at experiments with one, or even several, MUAVs would benefit from a simpler, potentially smaller, lighter and less expensive autopilot for their flying platforms.

In this paper, we present a minimalist control strategy for fixed-wing MUAVs that provides the three basic functionalities of airspeed, altitude and heading turnrate control while only using two pressure sensors and a single-axis rate gyro. To achieve this, we use reactive control loops, which rely on direct feedback from the sensors instead of full state information. In order to characterize the control strategy, it was implemented on a custom-made autopilot. With data recorded during flight experiments, we carried out a statistical analysis of step responses to altitude and turnrate commands as well as responses to artificial perturbations.

Keywords: Aerial Robotics, Neural and Fuzzy Control, Computer Vision
Abstract: This paper presents an implementation of two Fuzzy Logic controllers working in parallel for a pan-tilt camera platform on an UAV. This implementation uses a basic Lucas-Kanade tracker algorithm, which sends information about the error between the center of the object to track and the center of the image, to the Fuzzy controller. This information is enough for the controller to follow the object by moving a two axis servo-platform, regardless the UAV vibrations and movements. The two Fuzzy controllers for each axis, work with a rules-base of 49 rules, two inputs and one output with a more significant sector defined to improve the behavior of those controllers. The controllers have shown very good performances in real flights for statics objects, tested on the Colibri prototypes.

Keywords: Smart Actuators, Telerobotics, Physical Human-Robot Interaction
Abstract: Variable impedance actuation is characterized by the ability to independently set output force and output impedance for a robotic device. Adjusting the output impedance in real-time allows a device to better adapt to a variety of tasks, operate in human-like fashion, and support human safety. This paper focuses on a Series Clutch Actuator based on magnetorheological fluid which allows a fast, electrical change of the impedance while maintaining good force tracking. In particular the mechanical clutch can alter the high-frequency impedance, decoupling the motor inertia and thus reducing impact forces. We present the mechanical clutch design and a control system architecture to automatically adjust the fluid magnetization level and leverage the clutch benefits. Experiments verify torque tracking and impact force reduction both in autonomous and telerobotic operation. The actuator was designed and manufactured in collaboration with the Materials Design Institute at Los Alamos National Laboratory, and is tested in a single degree of freedom demonstration.

Keywords: Smart Actuators, Mechanism Design, Biomimetics
Abstract: Reported conjugated polymer actuators have typically been limited to bender or linear extender configurations. In this paper, we present a fiber-reinforced conjugated polymer actuator capable of torsional motion. By incorporating platinum fibers into the material matrix during the electrochemical fabrication process, we create anisotropy in the interaction between the fiber and the material matrix, resulting in torsion and other associated deformations upon actuation. A nonlinear elasticity-based model is utilized to capture the actuator performance for both small and large deformations. The effectiveness of the model is verified through comparison with experimental results.

Keywords: Smart Actuators
Abstract: A poly vinyl chloride (PVC) gel actuator shows great potential for use as an artificial muscle because of such positive characteristics as movement in the air, large deformation, and being lightweight. A bending type actuator using PVC gel was studied previously. We have proposed the structure of a contraction type actuator to construct an artificial muscle, and we have conducted some experiments using the single-layer PVC gel actuator. In this study, we investigate the characteristics of the multi-layer PVC gel actuator experimentally and evaluate its specifications in terms of the composition of PVC gel and the structure of the mesh electrode. The experimental results showed that the contraction rate of the actuator was about 14%, the response rate was 7Hz, and the output force was 4kPa. Also, we found that the stiffness of the actuator increased as the applied dc field increased such as human muscle. The characteristics of the PVC gel actuator are shown to be very effective for constructing an artificial muscle.

Keywords: Smart Actuators, Physical Human-Robot Interaction
Abstract: For several decades now, the robotics industry has postulated the emergence of a new breed of manipulators capable of safely interacting with humans. The integration of robots into human environments has always possessed a unique set of challenges. The primary concern has always been for the safety of the human coworkers. Insuring their safety has led to the desire to design manipulators with intrinsic safety characteristics. Specifically, it is noted that modern ‘human-safe’ manipulators are successful if they have minimized both their weight and reflected actuator inertia. The leading research accomplishing this relies on complex actuation systems. Such systems commonly suffer from degraded performance and high cost of development. Magneto- and Electro-Rheological fluids are a class of smart-materials that can instantaneously, and reversibly alter their rheological properties under the influence of an applied field. Devices developed with such fluids are known to possess superior torque-to-inertia characteristics over conventional servo systems. Moreover, their simple mechanical construction suggests that manipulators using such devices could be developed at a lower cost. In this paper, we will discuss the potential benefits rheological fluids can bring to the field of human friendly manipulators.

Keywords: Smart Actuators, Mechanism Design
Abstract: A conically shaped Dielectric Elastomer (DE) linear actuator is presented which is obtained by coupling a DE film with a compliant mechanism. The compliant mechanism is designed, by means of a pseudo-rigid-body model, to suitably modify the force generated by the elastomer film. The resulting actuator provides a nearly constant force along the entire actuator stroke when the DE film is activated and returns to an initial rest position when the DE film is deactivated. Experimental activity fully validates the proposed concept. Possible applications of this kind of actuator are Braille cells, light weight robots and haptic devices.

Keywords: Legged Robots, Dynamics
Abstract: This paper presents an approach for the closed-loop control of actuated biped that allows natural looking and energy efficient walking. Rather than prescribe kinematic trajectories or kinematic constraints, the approach is based on the prescription of state dependent torques that ”encourage” patterned movement. Some of the prescribed torques are referenced to the inertial reference frame, which largely decouples the angular dynamics of the robot, and as such greatly simplifies the selection of control parameters. Implementation of torques from the inertial coordinate frames is enabled by a joint torque computation which is motivated by Gauss’s principle of least constraint. The proposed approach is implemented in simulation on an anthropomorphic biped, and is shown to quickly converge to a natural-looking gait limit cycle. Simulations are conducted with various control parameters and different initial conditions. The authors also show that walking speed can be altered in a simple manner by varying two intuitive controller parameters. The mechanical cost of transport computed on a representative dynamic walk is used to validate energy efficiency of the proposed control approach.

Keywords: Legged Robots, Humanoid Robots, Parallel Robots
Abstract: Many researchers have studied on walking stability controls for biped robots. Most of them are highly accurate acceleration controls based on the mechanics model of the robot. However, the control algorithms are difficult to be applied to human-carrying biped robots due to modeling errors. In the previous report, we proposed the landing pattern modification method, but it had a problem that a foot landing-impact increased when a walking speed became fast. So, we propose a new terrain-adaptive control that can reduce a landing-impact force. To increase a concave terrain adaptation, we set a target landing position beneath a reference level. To reduce the landing-impact force, we change the position gain control value to a small value at a swing phase. Moreover, we set landing-foot speed at zero after detecting a foot-landing by the force sensor mounted on a foot. To follow uneven terrain, a virtual spring is installed to the vertical direction after detecting a foot-landing on a ground, and a virtual compliance control is applied to the roll and pitch axes. In a stable walk while carrying a 65 kg human on uneven terrain, the new control method decreased the landing-impact force than the previous terrain-adaptive control.

Keywords: Legged Robots, Adaptive Control, Biologically-Inspired Robots
Abstract: In this paper, we apply an energy saving control method to a simulation model that includes some dynamics of biped walking robots. This control method was proposed by the authors, and is based on resonance of multi-joint robots. An advantage of the control method is to work well without using exact parameter values of the controlled systems nor huge numerical calculations. This paper discusses how to apply the proposed control method to walking motions as a first step to realize energy saving biped robots. For this purpose, we consider some dynamics of the biped robots. Simulation results showed that the proposed control method can generate energy saving walking motions.

Keywords: Legged Robots, Dynamics, Motion Control
Abstract: In the passive dynamic walking proposed by McGeer, mechanical energy lost by heel strike is restored by transporting potential energy to kinetic energy as walking down a slope. When energy input is large such as an angle of slope is steep, bifurcation of walking period occurs. In parametric excitation walking, which is one method to realize passive dynamic-like walking on level ground, bifurcation has also been observed when walking speed is fast. Recently, Asano et al. have shown that bifurcation exerts an adverse influence upon walking performance by using rimless wheel model. In this paper, we apply delayed feedback control (DFC) originally used in chaos control to parametric excitation walking to suppress bifurcation. We show in numerical simulation that the proposed method makes two-period walking to one-period walking, and energy efficiency is improved. The analyses using Poincare map reveal that the one-period walking with DFC is unstable periodic orbit and that the robot dealt in this paper satisfies the sufficient condition of applicability of DFC.

Keywords: Legged Robots, Motion Control, Humanoid Robots
Abstract: A stable non-linear oscillator for autonomous biped stepping control is designed in a top-down manner by morphing standing regulator dynamics. It resolves three problems which have been on the conventional artificial CPG approaches, namely, 1) how to unify it with the standing control, 2) the controller parameter tuning with complicated networked unit oscillators, and 3) a design of an extra sensory feedbacks to be superimposed for stabilization. The proposed control is built upon the stabilizability-maximized COM-ZMP regulator developed by the author and only a single parameter seamlessly connects it to a stable limit cycle without degrading the stabilization performance. By synchronizing the foot-lifting with a limit cycle of ZMP, a stable periodic alternate stepping is achieved. Since it is free from time-driven trajectory, it is expected to be a fundamental technique to build robust autonomous biped controllers.

Keywords: Navigation, Motion Control, Wheeled Robots
Abstract: The article proposes a feedback control system for real-time navigation and obstacle avoidance that is made of two components: (i) a sensor-based, real-time model that generates and periodically updates the path on line in order to avoid both known and unforeseen obstacles, and (ii) a feedback-control model that is capable of driving a unicycle vehicle along the collision free path. The system has some unique characteristics, among which it requires very few computational resources as a consequence of its extreme simplicity. In spite of this, it is formally demonstrated to be asymptotically stable, as well as computationally efficient to be implemented in real-world scenarios where obstacles are not known, and possibly move in the environment.

Keywords: Navigation, Motion Control, Service Robots
Abstract: The article proposes a new feedback control model that allows path tracking for unicycle vehicles. With respect to other models in literature, the model measures only the distance between the vehicle and the path, whereas it ignores the vehicle's orientation. In spite of this, it allows to regulate to zero both the distance to the path and the difference between the vehicle's orientation and the tangent to the curve, and it is asymptotically stable. The model can be used to track a generic path which can be expressed as a curve in the Cartesian Space through its implicit equation. A formal description of the model is given, by outlining all its properties.

Keywords: Evolutionary Robotics, Autonomous Agents, Behaviour-Based Systems
Abstract: A variety of machine learning techniques have been employed to automatically create control algorithms for autonomous vehicles. Much research has focused on various ``black box'' approaches, in which the synthesized or learned control algorithms perform well when tested, but are difficult or impossible to analyze and understand. This paper presents the use of the ADATE system to evolve a control algorithm based on a racing car simulator. The system evolved compact and analyzable yet sophisticated control algorithms capable of driving millions of randomly generated tracks at high speeds without ever driving off the road. The approach presented is likely to be applicable to most automatic control problems, given a set of training examples and a suitable software simulator.

Keywords: Navigation, Nonholonomic Motion Planning, Intelligent Vehicles
Abstract: Most autonomous mobile agents operate in a highly constrained environment. Despite significant research, existing solutions are limited in their ability to handle heterogeneous constraints within highly dynamic or uncertain environments. This paper presents a novel maneuver selection technique suited for both 2D and 3D environments with highly dynamic maneuvering constraints and multiple mobile obstacles. Agents may have any arbitrary set of nonholonomic control variables; maneuvers can be constrained by a broad class of function inequalities, including time-dependent constraints involving nonlinear relationships between controlled and agent-state variables. The resulting algorithm has been implemented to run in real time using only a fraction of the CPU's capacity on an ordinary notebook computer and performs well in a number of taxing simulated situations.

Keywords: Navigation, Nonholonomic Motion Planning, Wheeled Robots
Abstract: This paper describes a novel method of path following for wheeled mobile robots. A number of virtual manipulators mounted on the robot are used to make the robot poses which satisfies both of trajectory tracking and collision avoidance. This method can calculate robot poses by using a single jacobi matrix despite of coping with several manipulators. We also presents about the method of tracking stabilization by using a singularity-avoiding criteria. Effectiveness of the proposed method is proven by means of simulation in both cases of omnidirectional wheelbase and 2 wheeled mobile base.

Keywords: Visual Tracking, Intelligent Vehicles
Abstract: In this paper, we propose a co-learning particle filter approach for vehicle tracking, which is very important for intelligent vehicle. The proposal distribution of the particle filter is a combination of an extra support vector machine (SVM) detector and the motion prior. Previous works focusing on how to online update the detector or the observation likelihood using the tracking results. These approaches belong to ``self-learning" fashion and easily tend to drift. The major difference between the proposed approach and previous works is that the SVM detector and the likelihood function can be mutually updated in a co-learning manner. By adopting the co-learning technology, the unlabelled samples which are generated during tracking are utilized to progressively modify the SVM detector and update the observation likelihood; therefore the resulting tracker is more robust and effectively avoid the drift problem. Finally, the performance of the proposed approach is evaluated using extensive real visual tracking examples.

Keywords: Visual Tracking, Computer Vision
Abstract: Abstract—Although primates can facilely maintain long-duration tracking of an object without infection of occlusion or other near similar distracters, it remains a challenge for computer vision system. Studies in psychology suggest that the ability of primates to focus selective attention on the spatial properties of an object is necessary to observe object quickly and efficiently while focus selective attention on the feature properties of object is necessary to render it more prominent from the distracters. In this paper, we propose a novel spatial-feature attentional visual tracking (SFAVT) algorithm to encode both. In SFAVT, tracking is treated as an on-line binary classification problem where spatial attention is employed in early selective procedure to construct foreground/background appearance model by identifying image patches with good localization properties, and in late selective procedure to update models by maintaining image patches with good discrimitive motion properties. Meanwhile, feature attention works in mode seeking procedure to help select feature spaces that best separate a target from background. The on-line tuned adaptive appearance models by those selected feature spaces are used to train a classifier for target localization, then. Experiments under various real-world conditions show that this algorithm is able to track an object influenced by dramatic distracters while is of comparable time efficiency with meanshift

Keywords: Visual Tracking, Computer Vision
Abstract: Tracking multiple people in crowded and cluttered dynamic scenes is a very difficult task in robotic vision due to the highly frequent occlusion and lack of visibility of objects. In this paper, we present a manifold learning based multiple people tracking approach with occlusion reasoning to solve this problem. In our previous work, a new Intrinsic Variable Preserving Manifold Learning (IVPML) method is proposed, by which the continuity of the intrinsic motion variables for tracking is preserved on a new manifold after dimensionality reduction. In this paper, the IVPML method is extended to be applied to tracking multiple people with occlusion situations. Associated with spatio-temporal continuity of tracking and IVPML method, a novel robust occlusion reasoning method is proposed during the alternations of multiple people. For occlusion recovery, region covariance representation including both spatial and statistic properties of objects are used to detect people after occlusion. The multiple people tracking method has been successfully applied to mobile robotic visual tracking system in several complicated environments. Comparisons and experimental results have shown the effectiveness of the new algorithm in various situations.

Keywords: Visual Tracking, Surveillance Systems, Computer Vision
Abstract: This paper addresses the problem of tracking a planar region of the scene using an uncalibrated omnidirectional camera. Omnidirectional cameras are a popular choice of visual sensors in robotics because the large field of view is well adapted to motion estimation and obstacle avoidance. The novelty of this work resides in simplifying the calibratin phase by providing a direct approach to tracking without any prior knowledge of the camera, lens or mirror parameters. We deal with a nonlinear optimization problem that can be solved for small displacements between two images like those acquired at video rate by a camera mounted on a robot. In order to assess the performance of the proposed method, we perform experiments with synthetic and real data.

Keywords: Visual Tracking, Computer Vision
Abstract: Tracking of the upper human body is one of the most interesting and challenging research fields in computer vision and comprises an important component used in gesture recognition applications. In this paper a probabilistic approach towards arm and hand tracking is presented. We propose the use of a kinematics model together with a segmentation of the parameter space to cope with the space dimensionality problem. Moreover, the combination of particle filters with hidden Markov models enables the simultaneous tracking of several hypotheses for the body orientation and the configuration of each of the arms.

Keywords: Humanoid Robots, Dynamics, Control Architectures and Programming
Abstract: This paper presents a new control architecture for compliant motion control and safe physical interaction between humanoid robot and human. It is realized by the Torque Transformer, which enables the implementation of joint torque control on joint position controlled robots. In this method, torque control is accomplished by converting desired joint torque into instantaneous increments of joint velocity command. This approach was experimentally implemented on the physical humanoid robot, HONDA ASIMO’s upper body control. The Operational Space Formulation was applied to account for the dynamics of the system. The ZMP based stable balance controller of ASIMO was integrated to control the lower body of the robot. In this framework, dynamics control by the torque transformer and stable position based balance controller are connected and coordinated together on the position controlled humanoid robot. The paper presents modeling process of the transformer, whole body controller and the results of the implementation which demonstrate the effectiveness of this approach.

Keywords: Humanoid Robots, Legged Robots, Motion Control
Abstract: This paper describes a real-time walking control system developed for the biped robots JOHNNIE and LOLA. Walking trajectories are planned on-line using a simplified robot model and modified by a stabilizing controller. The controller uses hybrid position/force control in task space based on a resolved motion rate scheme. Inertial stabilization is achieved by modifying the contact force trajectories. The paper includes an analysis of the dynamics of controlled bipeds, which is the basis for the proposed control system. The system was tested both in forward dynamics simulations and in experiments with JOHNNIE.

Keywords: Micro/Nano Robots, Biologically-Inspired Robots, Legged Robots
Abstract: The final goal of this work is the development of functional rubber sheets with micro rubber structure such as friction free, adhesion, and impact adsorption rubbers, etc. In previous report, we reported a micro rubber structure realizing flexible passive walking with 3 v-shaped units consisting of 4 legs to achieve very low friction. In this second report, we show the miniaturization and integration of this structure to realize a rubber sheet with 64 legs by micro rubber molding process using stereo lithography method. The prototype is designed and fabricated, and tested. Under some conditions, the 64 legged rubber sheet realizes flexible passive walking on a sloping road successfully.

Keywords: Humanoid Robots
Abstract: This paper presents a standing balance controller that explicitly handles pushes. We employ a library of optimal trajectories and the neighboring optimal control method to generate local approximations to the optimal control. We take advantage of a parametric nonlinear optimization method, SNOPT, to generate initial trajectories and then use Differential Dynamic Programming (DDP) to further refine them and get their neighboring optimal control. A library generation method is proposed, which keeps the trajectory library to a reasonable size. We compare the proposed controller with an optimal controller and an LQR based gain scheduling controller using the same optimization criterion. Simulation results demonstrate the performance of the proposed method.

Keywords: Humanoid Robots, Animation and Simulation, Kinematics
Abstract: This paper presents an approach to control gaits of humanoid bipedal robots in operational space without reference trajectories. This control strategy is based on the planning of the sequential events during the walking process. The aim of this study is to propose a new control strategy which is more reactive, permits a precise coordination of both legs during the double stance phase and the generation of dynamic 3D walking of an anthropomorphic biped with flexible feet. Based on homogeneous transformation matrices, the control strategy integrates three aspects in one unified representation: structural parameters of the robot, measurements given by sensors, planning of the sequential events during the different stages of the walk.

Keywords: Cognitive Human-Robot Interaction, Navigation
Abstract: Current fully autonomous robots are unable to navigate effectively in visually complex environments due to limitations in sensing and cognition. Full teleoperation using current interfaces is difficult and the operator often makes navigation mistakes due to lack of operating environment information and a limited field of view. We present a novel method for combining the sensing and cognition of a robot with that of a human. Our collaborative approach is different from most in that we address bi-directional considerations. It provides the human a mechanism to supplement the robot’s capabilities in a new and unique way and provides novel forms of feedback from the robot to enhance the human’s understanding of the current state of the system and its intentions.

Keywords: Human Performance Augmentation, Physical Human-Robot Interaction, Cooperating Robots
Abstract: This paper discusses skillful role divisions of coordinated motion between two agents in a crank-rotation task. The roles for coordination, called ``dynamical role division," emerge from dynamic interaction between the agents, through which each agent comes to play a specialized role without conscious understanding. This paper also proposes a novel approach to applying this latent skill in coordinated motions to human-robot coordination, and showing the following advantages of this method: 1) controls of each agent's actions are simplified; 2) task performances are improved with a simple manner.

Keywords: Physical Human-Robot Interaction
Abstract: To realize the harmonious cooperation with the operator, the man-machine cooperative system must be esigned so as to accommodate with the characteristics of the operator’s skill. One of the important considerations in the skill analysis is to investigate the switching mechanism underlying the skill dynamics. On the other hand, the combination of the feedforward and feedback schemes has been proved to work successfully in the modeling of human skill. In this paper, a new stochastic switched skill model for the sliding task, wherein a minimum jerk motion and feedback schemes are embedded in the different discrete states, is proposed. Then, the parameter estimation algorithm for the proposed switched skill model is derived. Finally, some advantages and applications of the proposed model is discussed.

Keywords: Physical Human-Robot Interaction, Cognitive Human-Robot Interaction, Adaptive Control
Abstract: Direct physical human-robot interaction has become a central part in the research field of robotics today. To use the advantages of the potential for humans and robots to work together as a team in industrial settings, the most important issues are safety for the human and an easy way to describe tasks for the robot. In this work, we present an approach of a hierarchical structured control of industrial robots for joint-action scenarios. Multiple atomic tasks including dynamic collision avoidance, operational position, and posture can be combined in an arbitrary order respecting constraints of higher priority tasks. The controller flow is based on the theory of orthogonal projection using nullspaces and constraint leastsquare optimization. To proof the approach, we present three collaboration scenarios between a human and an industrial robot.

Keywords: Programming Environment, Physical Human-Robot Interaction, Telerobotics
Abstract: This paper focuses on the simplification of the on-line programming process of industrial robots. It presents in detail the input part of a modular on-line programming environment presented as overview in [1]. Main concept of this programming environment is an intuitive way of moving and teaching robots, while supporting the user with assisting algorithms like collision avoidance and automatic path planning. Goal is the combination of different approaches from tele-operation, programming by demonstration, Virtual Reality and off-line programming, and to reuse them in a new fashion on-line on the shop-floor. This paper presents some ideas and concepts, how input devices for robot programming could look like and how to use them to set up an intuitive manual motion control of the robot.

Keywords: Mapping, Motion Control
Abstract: This paper presents a novel approach, compressive mobile sensing, to use mobile sensors to sample and reconstruct sensing fields based on compressive sensing. Compressive sensing is an emerging research field based on the fact that a small number of linear measurements can recover a sparse signal without losing any useful information. Using compressive sensing, the signal can be recovered by a sampling rate that is much lower than the requirements from the well-known Shannon sampling theory. The proposed compressive mobile sensing approach has not only the merits of compressive sensing, but also the flexibility of different sampling densities for areas of different interests. A special measurement process makes it different from normal compressive sensing. Adopting importance sampling, compressive mobile sensing enables mobile sensors to move adaptively and acquire more samples from more important areas. A motion planning algorithm is designed based on the result of sparsity analysis to locate areas of more interests. At last, experimental results of 2-D mapping are presented as an implementation compressive mobile sensing.

Keywords: Mapping, Service Robots, SLAM
Abstract: We present an approach to the problem of 3D map building in urban settings for service robots, using three dimensional laser range scans as the main sensor data input. Our system is based on the probabilistic alignment of 3D point clouds employing a delayed-state information-form SLAM algorithm, for which we can add observations of relative robot displacement efficiently. These observations come from the alignment of dense range data point clouds computed with a variant of the iterative closest point algorithm. The datasets were acquired with our custom built 3D range scanner integrated into a mobile robot platform. Our mapping results are compared to a GIS-based CAD model of the experimental site. The results show that our approach to 3D mapping performs with sufficient accuracy to derive traversability maps that allow our service robots navigate and accomplish their assigned tasks on a urban pedestrian area.

Keywords: Mapping, Localization, Sensor Fusion
Abstract: In this paper, we propose a system which reconstructs the environment with both color and 3D information. We perform extrinsic calibration of a camera and a LRF (Laser Range Finder) to fuse 3D information and color information of objects. We also formularize an equation to measure the result of the calibration. Moreover, we acquire 3D data by rotating 2D LRF with camera, and use ICP (Iterative Closest Point) algorithm to combine data acquired in other places. We use the SIFT (Scale Invariant Feature Transform) matching for the initial estimation of ICP algorithm. It offers accurate and stable initial estimation robust to motion change compare to odometry. We also modify the ICP algorithm using color information. Computation time of ICP algorithm can be reduced by using color information.

Keywords: Mapping, Localization
Abstract: Map information is important for path planning and self-localization when mobile robots accomplish autonomous tasks. In unknown environments, mobile robots should generate an environment map by themselves. Then, we propose a method for 3D environment modeling by a mobile robot. For environmental measurement, we use a single omni-directional camera only. We propose a new estimation method of camera motions for improvement in measurement robustness and accuracy. The method takes advantage of a wide field of view of an omni-directional camera. Experimental results showed the effectiveness of the proposed method.

Keywords: Navigation, Localization, Computer Vision
Abstract: In this paper, we describe a new approach which uses scale-invariant image features to estimate the motion of a stereo head. These point features are matched between pairs of frames and linked into image trajectories at video rate, generating what it is called visual odometry, i.e. motion estimates from visual input alone. With respect to previously proposed approaches, the main novelty of our proposal is that the matching between sets of features associated to stereo pairs and between sets of image features associated to consecutive frames are conducted by means of a fast combined constraint matching algorithm. Besides, the efficiency of the approach is increased by using a closed-form solution to estimate the final robot displacement between consecutive acquired frames. We have tested the proposed approach for navigational purposes in a real environment. Experimental results demonstrate the performance of the proposal.

Keywords: Learning and Adaptive Systems, Motion Control
Abstract: Robot skills are usually learned from the so-called learning-from-human-demonstration methods. However, with the limitation of robot motor capability, a robot may not be able to duplicate human motor skills with the same motor performance. To alleviate the problem, one of the possible solutions is to know robot motor capability in advance. Thus, we develop a quantitative measure of a robot motor system, called a pseudo index of motor performance (pIp), and utilize it to compare with the index of performance (Ip) of a human motor system. To investigate the Ip, we propose an information-theory-based method to characterize a robot motor system. Computer simulations and experiments with a PUMA 560 robot will be conducted to validate the proposed information-theory-based method.

Keywords: Learning and Adaptive Systems, Biologically-Inspired Robots, Autonomous Agents
Abstract: To improve the flexibility of robotic learning, it is important to realize an ability to generate a hierarchical structure. This paper proposes a learning framework which can dynamically change the planning space depending on the structure of tasks. Synchronous motion information is utilized to generate modes and different modes correspond to different hierarchical structure of the controller. This enables efficient task planning and control using low-dimensional space. An object manipulation task is tested as an application, where an object is found and used as a tool (or as a part of the body) to extend the ability of the robot. The proposed framework is expected to be a basic learning model to account for body image acquisition including tool affordances.

Keywords: Learning and Adaptive Systems, Service Robots, Dexterous Manipulation
Abstract: In mobile manipulation, the position to which the robot navigates has a large influence on the ease with which a subsequent manipulation action can be performed. Whether a manipulation action succeeds depends on many factors, such as the robot's hardware configuration, the controllers the robot uses to achieve navigation and manipulation, the task context, and uncertainties in state estimation. In this paper, we present ARPlace, an action-related place which takes these factors, and the context in which the actions are performed into account. Through experience-based learning, the robot first learns a so-called generalized success model, which discerns between positions from which manipulation succeeds or fails. On-line, this model is used to compute a ARPlace, a probability distribution that maps positions to a predicted probability of successful manipulation, and takes the uncertainty in the robot and object's position into account. In an empirical evaluation, we demonstrate that using ARPlaces for least-commitment navigation improves the success rate of subsequent manipulation tasks substantially.

Keywords: Learning and Adaptive Systems
Abstract: The increasing complexity of modern robots makes it prohibitively hard to accurately model such systems as required by many applications. In such cases, machine learning methods offer a promising alternative for approximating such models using measured data. To date, high computational demands have largely restricted machine learning techniques to mostly offline applications. However, making the robots adaptive to changes in the dynamics and to cope with unexplored areas of the state space requires online learning. In this paper, we propose an approximation of the support vector regression (SVR) by sparsification based on the linear independency of training data. As a result, we obtain a method which is applicable in real-time online learning. It exhibits competitive learning accuracy when compared with standard regression techniques, such as nu-SVR, Gaussian process regression (GPR) and locally weighted projection regression (LWPR).

Keywords: Learning and Adaptive Systems, Motion Control, Dynamics
Abstract: This paper focuses on generation of feedforward torque for precise joint-trajectory tracking of a multi-joint robot arm with serially connected links. A proposed method called basis-motion torque composition, based on four arithmetical operations of time-series torque data for several motions, allows to generate feedforward torque for a motion whose final posture and time profile are specified. The torque-generation algorism is presented, and the experimental results by a two-joint robot arm are illustrated. The experimental results demonstrate that the tracking errors of angular velocities by the basis-motion torque composition tend to be smaller than those by the computed torque method.

Keywords: Computer Vision, Recognition, Cognitive Human-Robot Interaction
Abstract: The semantic robots of the immediate future are robots that will be able to find and recognize objects in any environment. They need the capability of segmenting objects in their visual field. In this paper, we propose a novel approach to segmentation based on the operation of fixation by an active observer. Our approach is different from current approaches: while existing works attempt to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Furthermore, our solution integrates monocular cues (color, texture) with binocular cues (stereo disparities and optical flow). Experiments with real imagery collected by our active robot and from the known databases[1] demonstrate the promise of the approach.

Keywords: Cognitive Human-Robot Interaction, Learning and Adaptive Systems, Computer Vision
Abstract: We present a general method for integrating visual components into a multi-modal cognitive system. The integration is very generic and can combine an arbitrary set of modalities. We illustrate our integration approach with a specific instantiation of the architecture schema that focuses on integration of vision and language: a cognitive system able to collaborate with a human, learn and display some understanding of its surroundings. As examples of cross-modal interaction we describe mechanisms for clarification and visual learning.

Keywords: Learning and Adaptive Systems, Sensor Fusion, Robotics in Construction
Abstract: Currently, there is a high demand for autonomous industrial production systems. This paper outlines the development of a cognitive system for autonomous robotic welding. This system is based on dimensionality reduction techniques and Support Vector Machines, allowing the system to learn to separate between acceptable and unacceptable welding results within one batch, and to transfer this ability to a batch with different workpiece properties. It does not aim at a complete and general relationship between all process variables and result quantities, since it has been demonstrated that this is not necessary to reduce significantly the costs of calibrating the welding system. The main objective is to examine a cognitive system that stabilizes robotic welding processes by learning how to improve at least one process steering variable. In order to evaluate and improve the cognitive system, an extensive experimental setup is realized and described. The ability to learn and autonomously adapt to changes in workpiece properties allows the system to reduce the time an expert needs, and relaxes the requirements with respect to workpiece tolerances.

Keywords: Computer Vision, Learning and Adaptive Systems, Recognition
Abstract: To fulfill the dream of having autonomous robots at home, there is a need for spatial representations augmented with semantic concepts. Vision has emerged recently as the key modality to recognize semantic categories like places (office, corridor, kitchen, etc). A crucial aspect of these semantic place representations is that they change over time, due to the dynamism of the world. This call for visual algorithms able to learn from experience while at the same time managing the continuous flow of incoming data. This paper addresses these issues by presenting an SVM-based algorithm able to (a) learn continuously from experience with a fast updating rule, and (b) control the memory growth via a random forgetting mechanism while at the same time preserving an accuracy comparable to that of the batch algorithm. We apply our method to two different scenarios where learning from experience plays an important role: (1) continuous learning of visual places under dynamic changes, and (2) knowledge transfer of visual concepts across robot platforms. For both scenarios, results confirm the effectiveness of our approach.

Keywords: Computer Vision, Recognition, Cognitive Human-Robot Interaction
Abstract: Learning to recognize objects from a small number of example views is a difficult problem of robot vision, of particular importance to assistance robots who are taught by human users. Here we present an approach that combines bottom-up recognition of matching patterns and top-down estimation of pose parameters in a recurrent loop that improves on previous efforts to reconcile invariance of recognition under view changes with discrimination among different objects. We demonstrate and evaluate the approach both in a service robotics implementation as well as on the COIL database. The robotic implementation highlights features of our approach that enable real-time pose tracking as well as recognition from views where figure ground segmentation is difficult.

Keywords: Haptics and Haptic Interfaces, Telerobotics, Virtual Reality and Interfaces
Abstract: High frequency contact accelerations convey important information that the vast majority of haptic interfaces cannot render. Building on prior work, we present an approach to haptic interface design that uses a dedicated linear voice coil actuator and a dynamic system model to allow the user to feel these signals. This approach was tested through use in a bilateral teleoperation experiment where a user explored three textured surfaces under three different acceleration control architectures: none, constant gain, and dynamic compensation. The controllers that use the dedicated actuator vastly outperform traditional position-position control at conveying realistic contact accelerations. Analysis of root mean square error, linear regression, and discrete Fourier transforms of the acceleration data also indicate a slight performance benefit for dynamic compensation over constant gain.

Keywords: Haptics and Haptic Interfaces, Recognition, Force and Tactile Sensing
Abstract: This paper describes a method for command recognition by a haptic interface on a human support robot. Feature quantities are derived from the contact trajectory when an operator runs his finger across the haptic interface. The robot then recognizes a command based on these derived feature quantities from the symbolized contact trajectory. Conforming the robot motion to the symbolized contact trajectory allows for intuitive operation of the robot. The experimental results indicate that novice operators using this interface can obtain high command recognition rates.

Keywords: Haptics and Haptic Interfaces, Virtual Reality and Interfaces
Abstract: The tactile display for handheld devices requires compact hardware and useful applications. To satisfy these points, we have proposed the concept of 'Virtual Active Touch' that implements virtual exploration with a cursor on a screen through a pointing-stick-type tactile interface. The objective of this study is to present three-dimensional shapes on a two-dimensional screen without force feedback devices. It is possible to present three-dimensional shapes such as a bump using a lateral force [1]. In order to represent human perception of geometric surface shape, instead of the lateral force, we use the cutaneous sensation of friction that occurs when a human finger strokes object surfaces. First, we confirmed that the Virtual Active Touch interface could present cutaneous sense of friction. Second, we evaluated the perception of surface height in the context of bumped shape induced by the friction display. The experimental results agreed with our expectation that faster and longer increases in friction sensation were perceived as higher bumped shapes.

Keywords: Haptics and Haptic Interfaces, Physical Human-Robot Interaction, Virtual Reality and Interfaces
Abstract: Paper presents an upgrade of a Phantom Premium 1.5 haptic device for use within a functional magnetic resonance imaging (fMRI) environment. A mechanical extension attached to the Phantom allows the haptic device to operate at a safe distance away from a high-density magnetic field of an fMRI scanner. The extended haptic system was subjected to a series of tests to confirm electromagnetic compatibility with the fMRI environment, for which key results are presented. With the extended fMRI compatible haptic platform a human brain activation during controlled upper limb movements can be studied. A virtual environment reaching task was programmed to study brain motor control functions. At the end of the paper a preliminary results of an ongoing neurophysiological study are presented.

Keywords: Personal Robots, Rehabilitation Robotics, Haptics and Haptic Interfaces
Abstract: It is often difficult for visually impaired persons to walk outside to his or her destination. In this paper, we develop a cane with a built-in haptic interface for use by visually impaired persons. The cane is paired with IC tags buried underground (e.g., under street pavement). The haptic interface is controlled with a position and velocity control system that accurately indicates four directions (forward, backwards, right and left). After evaluating the vibration in the haptic interface, we determined the optimal vibration frequencies indicating a specific direction were combinations of 5 (Hz) and 1 (Hz). Furthermore, the optimal repetition of vibrations was determined to be two times. By using these conditions, the four directions were recognized more than 95% of the time. It was also confirmed that the visually impaired person recognized the presented direction even when an IC tag was buried underground. In the future, a mechanism will be developed that will allow visually impaired persons to recognize directions more accurately even if they swing the cane in a controlled manner. In addition, we will integrate a route decision system into the cane equipped with the haptic interface.

Keywords: Legged Robots, Dynamics, Motion Control
Abstract: Parametric excitation walking is one of methods that realize a passive dynamic like walking on the level ground. In parametric excitation walking, up-and-down motion of the center of mass restores mechanical energy and sustainable gait is generated. Walking ability and walking performance strongly depend on the reference trajectory of the center of mass. In this paper, we propose an optimization method for the reference trajectory of parametric excitation walking. There are two problems for optimization. One is that search space of a reference trajectory is inherently infinite dimensional. Another is that it takes long simulation time to generate steady gait for a given reference trajectory. Therefore, the proposing optimization method adopts the following strategy. For the former, we confine the reference trajectory to the quartic spline curve and take the parameter of spline curve as decision variables. For the latter, we discretize the search space and adopt a local search method usually used in combinational optimization problems. We apply the proposed method to a kneed biped robot, and optimize the reference trajectory of its swing leg.

Keywords: Legged Robots, Biologically-Inspired Robots, Biomimetics
Abstract: In this study, we discuss the common stabilization mechanism underlying passive dynamic walking (PDW) and passive dynamic running (PDR), focusing on the feedback structures in analytical Poincare maps. To this end, we have derived linearized analytical Poincare maps for PDW and PDR, and analyzed these stabilities on two models, namely models with elastic elements and with stiff legs. Through our theoretical analysis, we have found an "implicit two-delay feedback structure", which can be seen as a certain type of two-delay input digital feedback control developed as an artificial control structure in the field of control theory, is an inherent stabilization mechanism in PDR appearing from the model with elastic elements, and two-period and fourperiod PDW appearing from with stiff legs. This mechanism is the key to adaptive function underlying phase transition phenomenon between PDW and PDR and period-doubling bifurcation phenomenon in PDW. To the best of our knowledge, this has not yet to be addressed and studied so far. Our results shed new light on the common underlying principle of passive dynamic locomotion, including biped PDW, biped PDR, and quadruped PDW.

Keywords: Legged Robots, Dynamics, Motion Control
Abstract: Limit cycle walkers utilizing their natural dynamics can achieve energy-efficient dynamic walking. Their heel-strike collision with the ground is generally modeled as an inelastic collision, and the discrete walking dynamics can be specified in the same manner as a rimless wheel by using the energy-loss coefficient and restored mechanical energy. Energy-loss coefficient is especially significant because it controls the gait efficiency and stability, but the value varies significantly according to the swing-leg retraction just prior to impact and robot's mass-distribution. This paper then mathematically investigates how energy-loss coefficient changes with respect to them, and discusses the effect on the gait efficiency and stability.

Keywords: Legged Robots, Humanoid Robots
Abstract: In our previous work, we have realized Virtual Slope Walking that a robot can walk on level ground as it walks down a virtual slope by leg length modulation. In this paper, we present the instantaneous leg extension model of Virtual Slope Walking to analyze the essentials of Virtual Slope Walking. It has two straight massless legs and a point mass body at the hip. The stance leg is extended instantaneously while the swing leg is swung and shortened actively. We demonstrate that this model can exhibit stable walking cycles on level ground. We obtain the sufficient conditions for the existence of the fixed point. We then illustrate the effect of the model parameters on the fixed point to show how the fixed point can be determined by adjusting the parameters. Further, we theoretically proved that the fixed point is asymptotically stable, meaning that it is independent on the initial conditions. The validity of the proposed model has been examined by numerical simulations.

Keywords: Legged Robots, Humanoid Robots, Underactuated Robots
Abstract: This paper deals with a discret-time control approach, proposed for the control of a five-link, four-actuator planar biped walker. The approach is based on the choice of a particular class of walk configurations that enables a full state controllability avoiding the need to use Poincar'{e}-like argumentation in the proof of motion's reproducibility (stability of limit cycles). Simulation results attest the efficiency of the proposed control approach.

Keywords: Force Control, Humanoid Robots, Biologically-Inspired Robots
Abstract: This paper presents a method of modeling and subsequently characterizing stochastically controlled actuator arrays. The actuator arrays are built from cells, each containing six piezoelectric actuators and an amplification structure; however the results can be generalized to actuator arrays using solenoids, pneumatic cylinders, or any other fast acting linear actuators. The cells are controlled using an all-on all-off Bi-stable stochastic process wherein all cells are given a common input probability (control) value which they use to determine whether to actuate or relax. Laying out the cells in different networks gives different actuator array properties, which must be found before the actuator arrays can be applied to manipulators. A method is provided to calculate actuator array properties such as: travel, required actuator strength/displacement, force range, force variance, and robustness for any actuator array configuration. Finally the properties of several illustrative examples are shown and a discussion covers the importance of the properties, trends between actuator array layouts and their properties, and the course of future work in the area.

Keywords: Force Control, Haptics and Haptic Interfaces, Dynamics
Abstract: Stability problems associated with haptics and robot control with obstacle avoidance are analysed. Obstacle avoidance algorithms are revised to accomplish stable re-design using absolute stability and passivity theory. A modification of potential functions for haptic rendering and obstacle avoidance allowing stable operation for high stiffness is proposed. Using strictly positive real (SPR) re-design, stable force interaction can be provided also for high stiffness of manipulated objects or obstacles. Using the SPR re-design, a successful passivity-based revision of the artificial potential function was made.

Keywords: Force Control, Dynamics, Physical Human-Robot Interaction
Abstract: In this paper, a position based impedance controller (i.e. admittance controller) is designed by utilizing measurements of a force/torque sensor, which is mounted at the robot's base. In contrast to conventional force/torque sensing at the end-effector, placing the sensor at the base allows to implement a compliant behavior of the robot not only with respect to forces acting on the end-effector but also with respect to forces acting on the robot's structure. The resulting control problem is first analyzed in detail for the simplified one-degree-of-freedom case in terms of stability and passivity. Then, an extension to the Cartesian admittance control of a robot manipulator is discussed. Furthermore, it is shown how the steady state properties of the underlying position controller can be taken into account in the design of the outer admittance controller. Finally, a simulation study of the Cartesian admittance controller applied to a three-degrees-of-freedom manipulator is presented.

Keywords: Force and Tactile Sensing, Legged Robots, Micro/Nano Robots
Abstract: Recently multi-legged walking robots are widely developed. For these robots to walk safely, a sole sensor with high performance is desired. In the present paper, an arrayed type tactile sensor made of flexible silicone rubber, which is based on micro-electro-mechanical-systems (MEMS) technology, was developed. This sensor was applied as a sole sensor of a legged mobile robot. By processing the force data from many sensing elements using neural networks, information of contact force, i.e., three dimensional x, y, and z components of force vector, was able to be detected, which was confirmed by both simulation and experiment.

Keywords: Wheeled Robots, Mechanism Design, Legged Robots
Abstract: In many fields employing robots, e.g., wheelchair robots, rescue robots, and construction robots, those which can move on rough terrain are desired. A robot with a simple mechanism and high mobility for all-terrain is discussed in this paper. A novel type of four-wheel-type mobile robot is developed, and its design is discussed from a functional viewpoint. In addition, strategies for moving on rough terrain are introduced, and its fundamental capability of moving on rough terrain is verified through simulations and experiments.

Keywords: Micro-manipulation, Telerobotics, Haptics and Haptic Interfaces
Abstract: This paper presents a 2D teleoperation task at microscales with force feedback. At this scale, two major problems arise while performing manipulation tasks: the lack of 3D real time visual feedback, and the difficulty to determine the interaction forces. Therefore, indications must be provided to help the user perform a given task. In this paper, we provide the user with intuitive force feedback, to improve objects' manipulation using a haptic device. Our platform is composed of a tipless beam manipulator, which is deformed when forces are applied to it. These deformations are measured using a laser. The force information we provide to the user is based on the raw beam's deformation measurement, and mechanical properties of the probe. It does provide the operator with indications about the interaction forces. This approach is validated by performing lateral and longitudinal rolling operations using microspheres with a radius of 25-micrometers. 2D rolling telemanipulation at microscale with force feedback is successfully demonstrated.

Keywords: Micro-manipulation, Micro/Nano Robots
Abstract: A two-fingered micro hand has been available for use for years and allows dexterous manipulation of a single cell: grabbing, positioning, rotating and releasing. The end-effector of this micro hand consists of two glass needles; however, the glass tips must be finely adjusted and the micro hand must be calibrated prior to use. Because these initial procedures require highly skilled human operators and a great deal of time, a fine adjustment module (FAM) has been developed for assisting with the fine adjustment work and was successfully shown to make the initial setup easier. However, problems with the calibration process and with the dependence on a user of the FAM control are still present. One means of improving the system for users is to automate the initial setup. The detection of the glass tips in a wide range of Z directions from a microscopic image having a small depth of focus requires robust calibration and must be possible using an automated FAM control. From this perspective, the tip position detection algorithm using the evaluation function, Image Quality Measurement (IQM), is proposed in this paper. Based on this algorithm, the automated initial setup method is explained and its effectiveness is experimentally evaluated.

Keywords: Distributed Robot Systems
Abstract: Recently, a great deal of interest has been developed in learning in multi-agent systems to achieve decentralized control. Machine learning is a popular approach to find controllers that are tailored exactly to the system without any prior model. In this paper, we propose a semi-decentralized reinforcement learning control approach in order to position and convey an object on a contact-free MEMS-based distributed-manipulation system. The experimental results validate the semi-decentralized reinforcement learning method as a way to design control laws for such distributed systems.

Keywords: Micro-manipulation, Micro/Nano Robots, Visual Servoing
Abstract: This paper describes the vision-based methods developed for assembly of complex and solid 3D MEMS (micro electromechanical systems) structures. The microassembly process is based on sequential robotic operations such as planar positioning, gripping, orientation in space and insertion tasks. Each of these microassembly tasks is performed using a pose-based visual control. To be able to control the microassembly process, a 3D model-based tracker is used. This tracker able to directly provides the 3D micro-object pose at real-time and from only a single view of the scene. The methods proposed in this paper are validated by an automatic assembly of fives silicon microparts of 400 µm x 400 µm x 100 µm on 3-levels. The insertion tolerance (mechanical play) is estimated to 3 µm. The weakness of this insertion tolerance allows to obtain solid and complex micro electromechanical structures without any external joining (glue, wending). Promising positioning and orientation accuracies are obtained who can reach 0.3 µm in position and 0.2 ° in orientation.

Keywords: Micro/Nano Robots, Range Sensing, Micro-manipulation
Abstract: Micro displacement measurement of the PZT actuator is a micro sensor which could measure the minute displacement in micron or nanometer level. In general, the sensor is required not to accommodate much space in order to save the room of measuring device. In this paper, a mechanical micro displacement sensor with smaller volume has been proposed. This paper focus on the whole process of this novel sensor from the working principle, parameter determine to the FEM simulation as well as the characteristic experiment and so on. This sensor can enlarge the displacement of the PZT by utilizing the lever principle and from strain gauges can perceive the variation without amplifying the noise. In this sensor, we use the flexure hinges as the rotation joints to obtain the expansion. Whatever the simulation results in FEM or the experiment data, both of which show that the sensor can perceive the displacement of the PZT actuator in micro/nano scale. Also, the characteristic experiment shows that the proposed sensor has a higher level linearity, resolution and lower error.

Keywords: Robotics in Hazardous Fields, Manipulation Planning, Sensor Fusion
Abstract: Development of pole climbing robots was a challenging area during last decade. Previously developed pole climbing robots were based on either continuous or step-by-step based climbing mechanisms. All of step-by-step based PCRs, have some aspects in common. They have two grippers at two sides which are connected together through a multi DOFs climbing mechanism. The climbing mechanism might be serial, parallel or hybrid (serial-parallel). In all these robots, to make each step, one gripper grasps the structure and acts as the base of the robot, while the other gripper acts as manipulator. Therefore if the base is not well positioned before grasping, or if its position and angle changed after grasping the structure due to torques and forces which has been applied to it, then the error on the base will cause an error on the manipulator since the movement of the manipulator is relative to the base. This error along with other error sources which will be described in this paper, will remain with the manipulator in the next step in which the manipulator changed its role as base of the robot. If not compensated, this error will accumulate in next steps and after a couple of steps the operator should stop the operation and manually calibrate the robot. Consequently an algorithm for autonomous self calibration and error compensation is necessary. The key issue is that in contrary with industrial robotic arms, in mobile robots which include an arm, the base of the robot is not fixed in a certain point and contains positioning errors and therefore it should be compensated. 3DCLIMBER is a running project in the University of Coimbra for developing a climbing robot with the capability of manipulating over 3D human-made structures. The preliminary test of the robot showed that it is extremely important to precisely place the grippers in the appropriate pose before grasping the structure. Otherwise the mechanism will be over defined resulting in extreme current pulling of the motors and ineffective gripping. This paper suggests an algorithm which compensates related positioning errors based on inclinometers which has been instrumented at ISR-UC by using 2 axes analog accelerometer chips. Developed inclinometers along with the filtering methods applied, guarantees a precision of 0.3 degree. The method is very tolerant to the effects caused by mechanical vibrations of the serial arm links, which normally happens during operation of a serial arm in a mobile robot. Such vibrations, as will be demonstrated, will not decrease the mentioned precision.

Keywords: Robotics in Hazardous Fields, Telerobotics, Multifingered Hands
Abstract: Large multi-fingered end-effectors have promise to provide the added dexterity needed for manipulation while decreasing the amount of special fixturing required for tooling and object manipulation common to remote handling operations in hazardous and unstructured environments such as those in the nuclear domain. This paper presents the integration of a heavy-duty three-fingered articulated hand with a Schilling Titan hydraulic manipulator that is part of a comprehensive telerobotics test bed. Experiments demostrated that a multi-fingered end effector approach has distinct benefits and advantages.

Keywords: Robotics in Hazardous Fields, Field Robots
Abstract: In this paper we investigate how a mobile robot equipped with tin dioxide gas sensors and an anemometer can use an online classification algorithm in order to improve the exploration strategy. The purpose of the platform is to establish the character of a gas source with accuracy while minimizing the time required for exploration. For this to be possible, the output of the classification algorithm is probabilistic, feeding in a sequence of posterior probabilities to a path planner. To further assist path planning, a 3d-ultrasonic anemometer is available which give indication on the average wind speed and direction. In addition to evaluating different olfaction driven path planning strategies, experimental validations also evaluate the classification algorithms and its application to different environments with varying characteristics.

Keywords: Robotics in Hazardous Fields, Service Robots, Field Robots
Abstract: This paper analyzes the potential to apply mobile service robots in offshore oil and gas producing environments. The required hardware and software components and abilities of such a mobile offshore inspection and manipulation robot are presented in this paper. Possible applications of mobile service robots in an offshore environment range from simple visual inspection tasks to physical intervention with the process equipment, e.g. for sample taking, valve turning, cleaning up minor obstructions, and operating control panels. The first prototype of a mobile offshore inspection robot is equipped with a robotic arm which carries a camera for visual inspection as well as various application sensors such as a microphone, gas and fire sensors. It is able of both, remote and autonomous inspection of industrial process equipment. In automatic mode the robot autonomously executes pre-programmed inspection tasks. The results of all inspection tasks are saved to a database and can be reviewed by the responsible operator in the central control room at any time. The evaluation of the first autonomous mobile robot that has ever been operated in offshore environments has proven the applicability of mobile robotics to offshore environments. Different types of inspection tasks (visual and acoustic inspection, gas measuring) have been programmed to and executed by the robot successfully without ever jeopardizing the safety of the platform or the platform personnel. The application of mobile robotics in offshore environments can reduce the level of manual human intervention required to operate a production facility thereby increasing the efficiency of the workforce, improving safety and working conditions, and improving the production economics. The successful evaluation of the first realization of a mobile inspection and manipulation robot has thus leveled the ground for future mobile robot installations in offshore environments.

Keywords: Robotics in Hazardous Fields, Mechanism Design
Abstract: A mobile mechanism with biped configuration is proposed for power transmission line inspection purpose. The wire-walking cycle of the designed mechanism composed of single-support phase and double-support phase. During the process of single-support phase, one foot hang on line and the other foot swing from rear to front to overcome obstacles on line and realize wire-walking locomotion. The novel mechanism designing enable the centroid of the robot concentrate on the hip joint to minimize the drive torque of hip joint and keep the robot stable during the single-support phase. And the centroid of the robot will be adjusted to concentrate to the other leg to start a new single-support phase. Both the forward kinematics model and inverse kinematics model are established in this paper for motion control. The feasibility of this concept is then confirmed by designing a real wire-walking robot and by performing experiment with a simulated line environment.

Keywords: Space Robotics, Intelligent Vehicles
Abstract: We introduce an autonomous planetary exploration software architecture being developed for the purpose of autonomous science target identification and surface sample acquisition. Our motivation is to maximise planetary science data return whilst minimising the need for ground-based human intervention during long duration planetary robotic exploration missions. Our Autonomous Science Target Identification and Acquisition (ASTIA) architecture incorporates a number of key software components which support 2D and 3D image processing; autonomous science target identification based upon science instrument captured data; a robot manipulator control software agent, and an architecture software executive. ASTIA is being developed and tested within our Trans-National Planetary Analogue Terrain Laboratory (PATLab). This provides an analogue Martian terrain, and a rover chassis with onboard manipulator, cameras and computing hardware. Experimentation results with ASTIA and our PATLab rover are presented.

Keywords: Space Robotics, Field Robots, Kinematics
Abstract: This paper describes the design and implementation of DAVID, a lunar vehicle developed for the European Space Agency (ESA) Lunar Robotics Challenge, presenting severe terrain negotiation and sample acquisition challenges. We discuss in some detail two of the main innovative aspects of our entry to the challenge, i.e. the locomotion system and the sample acquisition system.

Motivated by the challenge specifications, a range of different locomotion systems were considered, among which we chose a simple, rugged and effective wheeled system. We provide an account of the choice of five different types of wheels, which were designed, analyzed and experimentally tested in conditions similar to the challenge. The system eventually turned out to be very effective in negotiating 89% slopes of volcanic terrain on the challenge site, Mount Teide in Tenerife.

To reduce the distance to be traveled on the difficult terrain and avoid risks in reaching the lowest parts of a crater, the vehicle was endowed with an innovative sample acquisition system, i.e. a casting manipulator. Casting manipulation is a technique in which the end-effector is thrown, the sample material is acquired, and the end-effector is retrieved using a light tether that acts as a ``fishing line''. The casting manipulator developed for DAVID uses an innovative sling-like technique, capable to obtain longer and more precise casts than previous oscillating versions. The analysis and experimental verification of DAVID's robot sling are reported, demonstrating its effectiveness.

Finally, we give a brief account of the outcomes of the ESA Lunar Robotics Challenge, where our team came in second over other 8 teams that passed the final qualification phase.

Keywords: Space Robotics, Dynamics, Wheeled Robots
Abstract: The wheel slip ratio is an important state variable in terramechanics research and the control of planetary rovers. Definitions of the slip ratio for a wheel with lugs and methods of estimating it for all wheels onboard have seldom been attempted. This paper presents several definitions for the slip ratio of a lugged wheel, which can be interconverted by altering the shearing radius. Equations for calculating the longitudinal velocity and slip ratio of a wheel moving on rough terrain are deduced from the horizontal speed of the wheel’s axle. Wheel-soil interaction experiments were performed for two types of wheels with different radii and lugs of different heights. The drawbar pull, torque, and wheel sinkage were measured using sensors. These data confirmed the effectiveness of the proposed slip ratio definition methods. Furthermore, two slip ratio estimation methods are proposed and verified: a visual information-based method by analyzing the lug traces marked on the terrain with high precision, and a terramechanics-based method in which the equations for the vertical load and torque are solved to estimate the slip ratios of all wheels.

Keywords: Space Robotics, Computer Vision, Localization
Abstract: We study the problem of localizing a balloon in the atmosphere of Saturn's moon Titan by registering onboard imagery with orbital imagery. This is critical for both autonomous navigation purposes and acquisition and sampling of scientifically interesting sites. Because of Titan's atmospheric opacity, we require the ability to match combinations of visible, infrared (IR) and synthetic aperture RADAR (SAR) images. For both localization and direct use as a multi-modal data product for science analysis, match results must be sub-pixel accurate. We demonstrate the feasibility of matching orbital SAR data to visible and IR imagery and outline a framework for using this data as a navigation product. We demonstrate a technique to compensate for local distortions to enable accurate data registration in spite of differences in sensor return and imaging geometry. Finally, we show match results using both terrestrial imagery and the limited amount of available Titan data acquired by the Cassini orbiter and Huygens probe.

Keywords: Space Robotics, Biomimetics, Legged Robots
Abstract: Suspicion of water ice deposits in the lunar south-polar region have sparked new interest into the earth's smaller companion, and robotic crater sample return missions are being considered by a number of space agencies. The difficult terrain with inclination of over 30°, eternal darkness and temperatures of less than -173° C make this a difficult task. In this paper we present a novel, bio-inspired light-weight system design, which demonstrates a possible approach for such a mission. The robot managed to come first in the Lunar Robotic Challenge (LRC), organised by the European Space Agency (ESA) in October 2008. Using a remote operated robot, we demonstrated to climb into and out of a lunar-like crater with an inclination of more than 35° on loose substrate, and performed the collection and delivery of a 100 g soil sample without the aid of external illumination.