Seminar Series on Robotics and AI (Talk 9)
04/04/2022 15:34


Hong Kong Centre for Logistics Robotics



The Chinese University of Hong Kong

T Stone Robotics Institute

Department of Mechanical and Automation Engineering


Seminar Series on Robotics and AI

Talk 9, April 2022 

Robot Skill Learning and Human-like Control

Prof. Chenguang Yang

Affiliation University of the West of England

United Kingdom


Prof. Fei Chen 

The Chinese University of Hong Kong

Hong Kong

Date: 8 April 2022 (FRI) 

Time:  4pm-5pm (Hong Kong Time, GMT+8)

Mode: Online (Zoom ID will be provided after registration)


Expressing, learning and reusing skills as modularized ones can strengthen the generalization ability of skills and reusability. Human-Robot shared control combines the advantages of both human and robot. This talk will introduce our advance in the field of robot skill learning and human-robot shared control. We use control theory to model the control mechanism of motor neurons to assist us developing human-like robot controllers so that the robot can realize variable impedance control to adaptively physically-interact with the changing environment. We further propose a multi-task impedance control and impedance learning method used on a human-like manipulator with redundant degrees of freedom to achieve compliant human-robot interaction motor control. Learning from human demonstration methods are generally used to efficiently transfer modularized skills to robots using multi-modal information such as surface electromyography signals and contact forces, enhancing the effectiveness of skill reproduction in different situations. We have also developed an enhanced neural-network shared control system for teleoperation, which uses the redundancy of joint space to avoid collisions automatically. The operator does not need to pay attention to possible collisions during manipulation. Besides, with the help of deep learning, we designed a tool power compensation system for teleoperation surgery, thereby enhancing the performance of the force and motion tracking at both ends of the teleoperation system. Furthermore, this talk will also introduce our research on the topics of human-robot collaboration and skill generalization.


Professor Chenguang (Charlie) Yang is the leader of Robot Teleoperation Group of Bristol Robotics Laboratory, a Co-Chair of the Technical Committee on Bio-mechatronics and Bio-robotics Systems (B2S), IEEE Systems, Man, and Cybernetics Society, and a Co-Chair of the Technical Committee on Collaborative Automation for Flexible Manufacturing (CAFM), IEEE Robotics and Automation Society. He received PhD degree from the National University of Singapore (2010) and performed postdoctoral research at Imperial College London. He is a recipient of the prestigious IEEE Transactions on Robotics Best Paper Award (2012) and IEEE Transactions on Neural Networks and Learning Systems Outstanding Paper Award (2022) as lead authors. He has been awarded EPSRC Innovation Fellowship and EU FP-7 Marie Curie International Incoming Fellowship. He is a Fellow of British Computer Society and Higher Education Academy.  He serves as Associate Editor of a number of leading international journals including seven IEEE Transactions. His research interest lies in human robot interaction and intelligent system design. 

 All are Welcome!