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15th Annual Conference on Advances in Autonomous robotics systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

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Dynamics identification of a damped multi elastic link robot arm under gravity

Dynamics identification of a damped multi elastic link robot...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jörn Malzahn Rene Felix Reinhart Torsten Bertram Institute of Control Theory and Systems Engineering Technische Universität Dortmund Dortmund Germany Research Institute of Cognition & Robotics — CoR-Lab. Bielefeld University Bielefeld Germany

The infinite dimensionality, varying, uncertainties or even unknown boundary conditions render the derivation and - in particular - the identification of accurate dynamics models for elastic link robots tedious and error prone. This contribution circumvents these challenges by the prior application of a model-free inner loop oscillation damping controller before modelling the robot's dynamics. Then, the damped dynamics of a multi elastic link robot arm under gravity can be modelled with high accuracy. An analytical and a data-driven model for the damped dynamics are proposed and quantitatively compared. Both models can explain motor currents as well as link strain measurements in real-time. The paper includes an experimental model validation with different payloads in the entire workspace of the robot.

关键词： Joints Torque Strain Robots Payloads Oscillators Analytical models

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Terrain identification on a one-legged hopping robot using high-resolution pressure images

Terrain identification on a one-legged hopping robot using h...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jacob J. Shill Emmanuel G. Collins Eric Coyle Jonathan Clark Department of Mechanical Engineering Center for Intelligent Systems Control. and Robotics (CISCOR) Tallahassee FL USA Department of Mechanical Engineering Embry-Riddle Aeron University Daytona Beach FL USA Department of Mechanical Engineering Scansorial and Terrestrial Robotics and Integrated Design Lab (STRIDe) Tallahassee FL USA

For efficient and safe locomotion the gaits of legged robots should vary with the type of terrain. Hence, terrain surface classification is an important problem for this class of mobile robots. Prior research has developed approaches to proprioceptive terrain classification for both wheeled and limbed robots that use sensor measurements dependent upon the dynamics of the robot, which ultimately requires the classification system to be trained at a large number of operating conditions (e.g., vehicle speeds and loads). This research develops an approach to terrain identification based on pressure images generated through direct surface contact using a robot skin constructed around a high-resolution pressure sensing array. Terrain signatures for classification are formulated from the magnitude frequency responses of the pressure images. The methodology is used to train and test a classifier using dynamically measured pressure images from a one-legged hopping robot. Experimental tests yield high classification accuracies, which are independent with respect to changing robot dynamics (i.e., different leg gaits). The findings of this paper suggest the methodology can be extended to autonomous field robots, providing the robot with crucial information about the environment that can be used to aid stability over rough terrains and enhance motion planning over varying terrains.

关键词： Robot sensing systems Skin Legged locomotion Vectors Foot Accuracy

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Adaptive control of unmanned surface vessels matching an optimized reference model

Adaptive control of unmanned surface vessels matching an opt...

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IEEE International Conference on robotics and Biomimetics

作者： Chenguang Yang Rongxin Cui Zhijun Li Sanjay Sharma Xingang Zhao Center for Robotics and Neural Systems Plymouth University Ply-mouth UK The MOE Key Lab of Autonomous System and Network Control South China University of Technology Guangzhou China School of Marine Science and Technology Northwestern Polytechnical University Xi'an China School of Marine Science and Engineering University of Plymouth Plymouth UK Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781479973989

In this paper, adaptive control of unmanned marine surface vessel has been investigated in the presence of uncertain dynamics as well as external disturbance. Variable structure technique has been utilized in the control design to make the dynamic response and desired motion tracking as quickly as possible. In practice, usually the desired trajectories are given as step points, such that direct immediate tracking would cause large acceleration and huge control effort, while the latter may be out of the actuators' limitation. Therefore, a reference model approach is employed, such that instead of direct tracking of the desired set point, the control objective becomes to shape the closed-loop dynamics to match a reference model. The reference model is built using optimization technique which tries to minimizes both tracking error and motion acceleration, and subsequently control effort. The smooth tracking is thus guaranteed in an optimal manner.

关键词： Tracking Acceleration Trajectory Adaptation models Performance analysis Mathematical model Dynamics

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Robust trajectory tracking control of a quadrotor UAV

Robust trajectory tracking control of a quadrotor UAV

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International Conference on systems and control (ICSC)

作者： Karima Benzaid Noura Mansouri Ouiddad labbani-Igbida Laboratory of Automatic Control and Robotics Constantinel University Constantine Algeria Modeling Information & Systems lab. University of Picardie Jules Verne Amiens France

In this paper, we present two control strategies of a quadrotor Unmanned Aerial Vehicle (UAV). The dynamics of the system is controlled to achieve a complex trajectory tracking. A controller using the integral backstepping is developed for the stabilization of the six degrees of freedom (6DoF) of the system. Furthermore, we propose a hybrid strategy by combining the integral backstepping and the PID linear controller. For this, we divide the dynamic system into two subsystems; each one with 3DoF. For the stabilization of the rotational dynamics, the PID controller is proposed. The Integral Backstepping is applied for the longitudinal, lateral and vertical position stabilization. Finally, some numerical simulations are conducted to illustrate the robustness of both strategies.

关键词： Backstepping Trajectory Vehicle dynamics Mathematical model Algorithm design and analysis Rotors Lyapunov methods

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Telemanipulation with the DLR/HIT II Robot Hand Using a Dataglove and a Low Cost Force Feedback Device

Telemanipulation with the DLR/HIT II Robot Hand Using a Data...

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Mediterranean Conference on control & Automation

作者： Minas V. Liarokapis Panagiotis K. Artemiadis Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens ASU Human-Oriented Robotics and Control (HORC) Lab School for Engineering of Matter Transport and Energy Ira A. Fulton Schools of Engineering Arizona State University

ISBN: (纸本)9781479909964

In this paper a series of teleoperation and manipulation tasks are performed with the five fingered robot hand DLR/HIT II. Two different everyday life objects are used for the manipulation tasks;a small ball and a rectangular object. The joint-to-joint mapping methodology is used to map human to robot hand motion, taking into account existing kinematic constraints such as synergistic characteristics and joint couplings. The Cyberglove II motion capture dataglove is used to measure human hand kinematics. A robot hand specific fast calibration procedure is used to map raw dataglove sensor values to human joint angles and subsequently through the mapping procedure, to DLR/HIT II joint angles. A novel low cost force feedback device is developed, in order for the user to be able to detect contact and perceive the forces exerted by the robot fingertips, during manipulation tasks. The design of the force feedback device is based on RGB LEDs that provide visual feedback and vibration motors that provide vibro-tactile feedback.

关键词： Telemanipulation Teleoperation Force Feedback Device Mapping Human to Robot Motion

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Mapping Human to Robot Motion with Functional Anthropomorphism for Teleoperation and Telemanipulation with Robot Arm Hand systems

Mapping Human to Robot Motion with Functional Anthropomorphi...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Minas V. Liarokapis Panagiotis K. Artemiadis Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens 9 Heroon Polytechniou Str Athens 15780 Greece ASU Human-Oriented Robotics and Control (HORC) Lab School for Engineering of Matter Transport and Energy Ira A. Fulton Schools of Engineering Arizona State University 501 E. Tyler Mall ECG 301 Tempe AZ 85287-6106 USA

ISBN: (纸本)9781467363563

In this paper teleoperation and telemanipulation with a robot arm (Mitsubishi PA-10) and a robot hand (DLR/HIT 2) is performed, using a human to robot motion mapping scheme that guarantees anthropomorphism. Two position trackers are used to capture position and orientation of human end-effector (wrist) and human elbow in 3D space and a dataglove to capture human hand kinematics. Then the inverse kinematics (IK) of the Mitsubishi PA-10 7-DoF robot arm are solved in an analytical manner, in order for the human's and the robot artifact's end-effectors to achieve same position and orientation in 3D space (functional constraint). Redundancy is handled in the solution space of the robot arm's IK, selecting the most anthropomorphic solution computed, with a criterion of "Functional Anthropomorphism". Human hand motion is transformed to robot hand motion using the joint-to-joint mapping methodology. Finally in order for the user to be able to detect contact and "perceive" the forces exerted by the robot hand, a low-cost force feedback device, that provides a mixture of sensory information (visual and vibrotactile), was developed.

关键词： Robot Arm Hand systems IK wrist

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Segregation in swarms of e-puck robots based on the Brazil nut effect

Segregation in swarms of e-puck robots based on the Brazil n...

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11th International Conference on Autonomous Agents and Multiagent systems 2012: Innovative Applications Track, AAMAS 2012

作者： Chen, Jianing Gauci, Melvin Price, Michael J. Groß, Roderich Natural Robotics Lab. Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom

ISBN: (纸本)9781627481564

When a mixture of particles with different attributes undergoes vibration, a segregation pattern is often observed. For example, in muesli cereal packs, the largest particles-the Brazil nuts-tend to end up at the top. For this reason, the phenomenon is known as the Brazil nut effect. In previous research, an algorithm inspired by this effect was designed to produce segregation patterns in swarms of simulated agents that move on a horizontal plane. In this paper, we adapt this algorithm for implementation on robots with directional vision. We use the e-puck robot as a platform to test our implementation. In a swarm of e-pucks, different robots mimic disks of different sizes (larger than their physical dimensions). The motion of every robot is governed by a combination of three components: (i) attraction towards a point, which emulates the effect of a gravitational pull, (ii) random motion, which emulates the effect of vibration, and (iii) repulsion from nearby robots, which emulates the effect of collisions between disks. The algorithm does not require robots to discriminate between other robots;yet, it is capable of forming annular structures where the robots in each annulus represent disks of identical size. We report on a set of experiments performed with a group of 20 physical e-pucks. The results obtained in 100 trials of 20 minutes each show that the percentage of incorrectly-ordered pairs of disks from different groups decreases as the size ratio of disks in different groups is increased. In our experiments, this percentage was, on average, below 0.5% for size ratios from 3.0 to 5.0. Moreover, for these size ratios, all segregation errors observed were due to mechanical failures that caused robots to stop moving. Copyright © 2012, International Foundation for Autonomous Agents and Multiagent systems (***). All rights reserved.

关键词： Multipurpose robots

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Task Discrimination from Myoelectric Activity: A Learning Scheme for EMG-Based Interfaces.

Task Discrimination from Myoelectric Activity: A Learning Sc...

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IEEE International Conference on Rehabilitation robotics

作者： Minas V. Liarokapis Panagiotis K. Artemiadis Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens 9 Heroon Polytechniou Str Athens 15780 Greece. ASU Human-Oriented Robotics and Control (HORC) Lab School for Engineering of Matter Transport and Energy Ira A. Fulton Schools of Engineering Arizona State University 501 E. Tyler Mall ECG 301 Tempe AZ 85287-6106 USA.

ISBN: (纸本)9781467360210

A learning scheme based on Random Forests is used to discriminate the task to be executed using only myoelectric activity from the upper limb. Three different task features can be discriminated: subspace to move towards, object to be grasped and task to be executed (with the object). The discrimination between the different reach to grasp movements is accomplished with a random forests classifier, which is able to perform efficient features selection, helping us to reduce the number of EMG channels required for task discrimination. The proposed scheme can take advantage of both a classifier and a regressor that cooperate advantageously to split the task space, providing better estimation accuracy with task-specific EMG-based motion decoding models, as reported in [1] and [2]. The whole learning scheme can be used by a series of EMG-based interfaces, that can be found in rehabilitation cases and neural prostheses.

关键词： Task Discrimination Activity

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