Biomimetic Adaptive and Learning Control with Application to Compliant Robots
Dr Yongping Pan
Senior Research Fellow, National University of Singapore, Singapore
– All Welcome –
The rapid population ageing has been pushing robotic research from industrial robots that are separated from humans to service robots that coexist and cooperate with humans. A key feature of service robots is that they may physically interact with humans so that safety is the foremost concern. Compliant actuation and compliant control are a natural way and an enabling technology toward safe and comfortable human-robot interaction (HRI), respectively. Conventional robotic systems usually need to increase control gains to compensate for high nonlinearities of the robot dynamics, which may destroy intrinsic compliance of robots, generate unsafe motions for HRI, and degrade closed-loop stability. On the contrary, biological systems implement compliant and robust control with low control gains such that all above drawbacks are avoided. In this talk, I will first introduce the concept of compliant robotics. And then, I will present my works in the development of biomimetic adaptive and learning control strategies and the application of the developed control strategies to compliant robots toward safe and comfortable HRI. Finally, I will outlook my future plans in bioinspired robot design and control.
Yongping Pan received the PhD degree in control theory and control engineering from the South China University of Technology, Guangzhou, China in 2011. He was a Control Engineer with the Santak Electronic Co., Ltd., US Eaton Group, Shenzhen, China, and the US Light Engineering Co., Ltd., Guangzhou from 2007 to 2008. From 2011 to 2013, he was a Research Fellow with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He became a Research Fellow of the Department of Biomedical Engineering, National University of Singapore, Singapore in 2013 and was promoted to be one of the two Senior Research Fellow of the department in 2016. His research spans automatic control, machine learning, and robotics, with a strong focus on nonlinear and adaptive control, neural networks and learning systems, and their applications to compliant robotics and human-robot interaction. He has authored or co-authored more than 80 peer-reviewed academic papers, including 66 refereed journal papers and 6 ESI Highly Cited Papers. His publications have attracted over 1600 and 950 citations in the Google Scholar and Web of Science, respectively, where the Field-Weighted Citation Impact issued by the Elsevier SciVal indicates that the publication impact is over 5 times higher than the average. Dr Pan has been invited as an Associate Editor or Editorial Board Member of 6 reputable refereed journals such as the IEEE Robotics and Automation Letters, Applied Soft Computing, and Frontiers in Neurorobotics. He is a Lead Guest Editor of the International Journal of Adaptive Control and Signal Processing. Besides, he has served as a Reviewer for over 50 refereed journals and a Committee Member for two international conferences.
For more information, please contact Prof Chun Wang