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International Conference on Information and automation (ICIA)

作者： Chenguang Yang Junshen Chen Zhijun Li Wei He Chun-Yi Su Center for Robotics and Neural Systems Plymouth University UK College of Automation Science and Engineering South China University of Technology Guangzhou China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Mechanical and Industrial Engineering Concordia University Montreal Canada

In this paper, we have developed a teleoperation method with novel features, such that the human operator could manipulate the telerobot using both physical and physiological means. Physiological studies have shown that our central neural system (CNS) is able to adapt muscle force, stiffness and damping to perform different tasks under various environments. However, there has been very little research in the robotics communities to incorporate human motor skills of muscle force, stiffness and damping adaptation into teleoperation. As a matter of fact, muscle activities regulated by CNS can be represented by surface electromyography (sEMG) measured by electrodes attached on the skin of human limbs. Therefore, sEMG based teleimpedance control has been recently developed to transfer the variable stiffness from human operator to a robot for flexible manipulation [1], [2], [3]. In this paper, we have developed a personalised variable gain control, whereas the control gain is set according to muscle activation extracted from sEMG signals, and force feedback is employed such that human operator is able to sense the circumstance in a haptic manner and to adapt muscle contraction subconsciously as if they are directly interacting with the environment. The proposed method enables an operator to adjust tracking speed and stiffness of the telerobot easily on the fly, and thus greatly improves a user's manipulation ability for delicate tasks, especially in the presence of motion amplification and varying payload on the telerobot. The effectiveness of the proposed approach has been tested and confirmed by comparative experiments, in which a 7-DOF (degrees of freedom) robotic arm of Baxter® robot is employed.

关键词： Force Manipulators Muscles Haptic interfaces Electromyography Robot sensing systems

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Teleoperated robot writing using EMG signals

Teleoperated robot writing using EMG signals

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International Conference on Information and automation (ICIA)

作者： Chenguang Yang Sai Chang Peidong Liang Zhijun Li Chun-Yi Su Center for Robotics and Neural Systems Plymouth University UK College of Automation Science and Engineering South China University of Technology Guangzhou P. R. China State Key Lab of Robotics Systems Harbin Institute of Technology Harbin P. R. China Department of Mechanical and Industrial Engineering Concordia University Montreal Canada

ISBN: (纸本)9781467391054

In this paper, we have developed a method to tele-control a robot arm to imitate human writing skills using electromyography (EMG) signals. The control method is implemented on the Baxter® robot with a brush attached on the endpoint of its arm to imitate human writing skills, and a MYO sensor is used to measure the surface electromyographic (sEMG) signals generated by contractions of human muscles involved in writing tasks. A haptic device Sensable® Omni is used to control the motion of the Baxter® robot arm, and V-Rep® is employed to simulate the movement of the arm and to calculate the inverse kinematic of Baxter® robot arm. All the communications for Baxter® robot, V-Rep simulator, Omni device and MYO are integrated in MATLAB®/Simulink®. The main test is to make the Baxter® arm following the movement of a human subject when writing with Omni stylus, and the EMG signals are processed using low pass filter and moving average technique to extract the smoothed envelope which is utilised to control the variation of position instead of variation of force along the vertical Z axis, so when the operator writes with force variations, the Baxter® can draw lines with variable thickness. This imitation system is successfully tested to make the Baxter® arm to follow the writing movement of the operator's hand and would have potential applications in more complicated human robot teleoperation tasks such as tele-rehabilitation and tele-surgery.

关键词： Electromyography Robot sensing systems Joints Phantoms Muscles Writing

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Teaching by Demonstration on Dual-arm Robot using Variable Stiffness Transferring

Teaching by Demonstration on Dual-arm Robot using Variable S...

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IEEE International Conference on robotics and Biomimetics

作者： Chenguang Yang Peidong Liang Zhijun Li Arash Ajoudani Chun-Yi Su Antonio Bicchi College of Automation Science and Engineering South China University of Technology Guangzhou China State Key Lab of Robotics Systems Harbin Institute of Technology China Department of Advanced Robotics Istituto Italiano di Tecnologia Italy and Interdepartmental Research Center "E. Piaggio" Faculty of Engineering University of Pisa Italy Department of Mechanical and Industrial Engineering Concordia University Canada

ISBN: (纸本)9781467396769

Teaching by demonstration (TbD) techniques have been extensively investigated in the recent decades to enable transferring various task skills from human to robots. The traditional TbD techniques focus on teaching motion trajectories that may be sufficient for routine tasks with fixed objects. While for interactive tasks in contact with dynamic environment and objects, e.g., the payload of a robot manipulator may change from one to another, teaching robot only by motion demonstration may cause undesired contact force and inefficiency in the task execution. In this paper, we present a novel TbD method enhanced by transferring the stiffness profile during human robot interaction (HRI). The method is developed on a bimanual robot, whereas one slave arm plays the role of the tutee, and the other master arm coupled with human demonstrator plays the role of tutor. A rendering algorithm is employed to provide demonstrator with force feedback via a purposely built coupling device according to the motion disparity between the two arms. The muscle surface electromyography (sEMG) signals collected during HRI is processed to extract the demonstrator's variable stiffness as well as hand grasping patterns. Comparative tests have been carried out on a bimanual Baxter robot for a lifting task with three different set-ups: i) TbD with predefined fixed stiffness;ii) TbD with demonstrator transferred variable stiffness without force feedback;and iii) TbD with demonstrator transferred variable stiffness with force feedback. Results show that the proposed TbD method performs best by transferring the demonstrator's physical interactive skill to the robot in a natural and efficient manner.

关键词： TbD proposed efficient

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Global Bounded Consensus of General Nonidentical Networks With Distributed Time-Delays

Global Bounded Consensus of General Nonidentical Networks Wi...

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IEEE Annual Conference on Decision and Control

作者： Xiuxian Li Housheng Su Chanying Li Zheng Wang Michael Z. Q. Chen Department of Mechanical Engineering The University of Hong Kong Pokfulam Hong Kong School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 PR China National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479978878

In this paper, global bounded consensus problem of general nonidentical networks with nonlinear dynamics and distributed time-delays is investigated, in which the distributed time-delays are distinct from each other. The global consensus exists in the sense of boundedness since complete consensus does not often exist in the nonidentical case. With the aid of constructing a Lyapunov-Krasovskii functional and utilizing the technique of integral partitioning, some sufficient delay-dependent conditions are derived to ensure that global bounded consensus is achieved ultimately. Finally, effectiveness of the theoretical result is illustrated by a numerical example.

关键词： Bounded Nonlinear Dynamics numerical example Distribute Automatic incident detection Distinct

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Quasi-Synchronization of the Heterogeneous Oscillator Dynamical Networks 33

Quasi-Synchronization of the Heterogeneous Oscillator Dynami...

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第三十三届中国控制会议

作者： WANG Zhengxin JIANG Guoping YU Wenwu CAO Jinde College of Science Nanjing University of Posts and Telecommunications College of Automation Nanjing University of Posts and Telecommunications Research Center for Complex Systems and Network Sciences and Department of MathematicsSoutheast University Faculty of Engineering King Abdulaziz University Department of Mathematics Faculty of ScienceKing Abdulaziz University

ISBN: (纸本)9781479947249

The paper investigates quasi synchronization of heterogeneous networks coupled with N nonidentical Duffing-type *** comparing with a virtual synchronization target which is a weighted average of the states of N oscillators,some sufficient criteria of quasi synchronization are ***,some simulations are given to verify the obtained theoretical results.

关键词： Heterogeneous networks,Coupled oscillator networks,Quasi synchronization,Duffing oscillator

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Opening remarks

2016 International Conference on Advances in Human Machine I...

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2016 International Conference on Advances in Human Machine Interaction, HMI 2016 2016年

作者： Nagaraja, Ch. Swamy, J. Nagendra Rajendra, J. Khan, M.S. Vishwanath Reddy, D.S. Manjunath, N. Dillmann, Ruediger Tarn, Tzyh Jong Zhao, Qianchuan Ammi, Mehdi Zuberek, Wlodek M. Sandhu, P.S. Patthira Newman, K. De Silva Liyanage, Chandratilak Hassan, Sohair Aly Aly Sun, Kien Wen Rahman, Md. Moshiur Ordoño, E. Evangelista Sharma, R.K. Mishra, Preeti Chandel, B.S. Singla, Ekta Petric, Tadej Zhong, Yu Jiglar, Janson Alemzadeh, Kazem Asokan, T. Tripathi, Animesh Tripathi, Manoj Ram, Swaminath Shrma, M.K. Panday, P.N. Kumar, Devendra Hinchey, Mike Stilman, Boris Suraj, Zbigniew Pal, Sankar K. Sasi, Sreela Rajan, Deepu Marshall, Roger G. Abraham, Ajith Peter S, David Paul, Vargheese Gopakumar, V. Dustdar, Schahram Soto, Sebastián Ventura Rausch, Andreas Angelis, Lefteris Nelson, Andrew L. Botzheim, Janos Bernardino, Heder Soares Zboril, Frantisek Ane, Bernadetta Kwintiana Maeda, Toshiyuki Sakalauskas, Virgilijus Hann, Garenth Lim King Samek, Jan Romero Salguero, José Raúl Varghese, Kuruvilla Kriksciuniene, Dalia Mathew, Jimson Reif, Wolfgang Mauri, Giancarlo Cabrerizo Lorite, Francisco Javier Özcan, Ender Cho, Sung-Bae Paily, Roy P. Rezankova, Hana Tudjarov, Boris Hong, Wei-Chiang De Oliveira, José Valente Flores Romero, Juan Jose Oskouei, Rozita Jamili Cicchetti, Antonio Roy, Chanchal Segura, Sergio Samuel, C. Mallet, Frédéric Mernik, Marjan Punnekkat, Sasikumar Waseemulla, A. Sri Devaraj Urs Educational Trust Bangalore India R. L. Jalappa Institute of Technology Doddaballapur Bangalore India Humanoids and Intelligence Systems Lab Kalsruhe Germany Electrical and Systems Engineering Washington University in St. Louis United States Deputy Director of Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing China Department of Computer Science CNRS/LIMSI Lab AMI Group France Memorial University St. John'sNL Canada RBIT and Bio-Technology India LR University Thailand University of Colorado at Boulder Boulder United States Faculty of Science University of Brunei Brunei University of Kuala Lumpur Malaysia National Chiao Tung University Taiwan EPR Centre Bangladesh Mapua Institute of Technology Philippines ARO CWC Lucknow India Mpec Kanpur India DSC DBS Kanpu India Indian Institute of Technology Ropar India Jozaf Stefan Institute Department of Automation Biocyernetics and Robotics Ljubljana Slovenia Robotics Institute Carnegie Mellon University Pittsburgh United States Faculty of Engineering University of Bristol United Kingdom Department of Engineering Design Indian Institute of Technology Madras India Lucknow Uni Lucknow India CSJM Uni Kanpur India UPPCB Lucknow India PCB Roorkee India Awadh Uni Faijabad India Agra Uni Agra India Lero University of Limerick Ireland University of Colorado Denver United States University of Rzeszow Poland Indian Statistical Institute Kolkata India Gannon University PA United States Nanyang Technical University Singapore Singapore Plymouth State University NH United States MIR Labs United States Cochin University of Science and Technology India State Project Facilitation Unit TEQIP Kerala India Technical University of Vienna Austria University of Cordoba Spain Clausthal University of Technology Germany Aristotle University of Thessaloniki Greece Androtics LLC TucsonAZ United States Tokyo Metropolitan University Japan Federal Unive

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Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot

Implementation and test of human-operated and human-like ada...

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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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Large scale image understanding with non-convex multi-task learning

Large scale image understanding with non-convex multi-task l...

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International Conference on Game Theory for Networks, GameNets

作者： Liang Li Chenggang Yan Xing Chen Shuqiang Jiang Seungmin Rho Jian Yin Baochen Jiang Qingming Huang University of Chinese Academy of Sciences Beijing China Department of Automation Tsinghua University Beijing China Academy of Mathematics and Systems Science CAS Beijing China National Center for Mathematics and Interdisciplinary Sciences Chinese Academy of Sciences(CAS) Beijing China Key Lab of Intell. Info. Process. Inst. of Comput. Tech. CAS Beijing China Department of Multimedia Sungkyul University Korea Department of Computer Shandong University Weihai China

ISBN: (纸本)9781479979035

Large scale image understanding is drawing more and more attention from the researchers and industry. Inspired by the game theory and machine learning algorithm, this paper proposes a semantic dictionary to solve the key problem of visual polysemia and concept polymorphism in the large scale image understanding. The semantic dictionary characterizes the probability distribution between visual appearances and semantic concepts, and the learning of semantic dictionary is formulated into a minimization problem of the payoffs, where the players adjudge their strategies (i.e. the probability distribution) at each iteration. Non-convex multi-task learning is introduced to solve the above optimization problem. Finally, the wide applications of semantic dictionary are validated in our experiments, including the large scale semantic image search and image annotation.

关键词： Semantics Optimization

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Model-order reduction of biochemical reaction networks

Model-order reduction of biochemical reaction networks

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European Control Conference (ECC)

作者： Shodhan Rao Arjan van der Schaft Karen van Eunen Barbara M. Bakker Bayu Jayawardhana Center for Systems Biology University of Groningen Johann Bernoulli Institute for Mathematics and Computer Science University of Groningen Department of Paediatrics Universitair Medisch Centrum Groningen Discrete Technology and Production Automation University of Groningen

ISBN: (纸本)9781479901890

In this paper we propose a model-order reduction method for chemical reaction networks governed by general enzyme kinetics, including the mass-action and Michaelis-Menten kinetics. The model-order reduction method is based on the Kron reduction of the weighted Laplacian matrix which describes the graph structure of complexes in the chemical reaction network. We apply our method to a yeast glycolysis model, where the simulation result shows that the transient behaviour of a number of key metabolites of the reduced-order model is in good agreement with those of the full-order model.

关键词： Mathematical model Kinetic theory Chemicals Vectors Reduced order systems Biological system modeling Biochemistry

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