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Plenary Speakers

Prof. Yongping Pan

Sun Yat-sen University, China



BIO: Dr. Yongping Pan is a Professor who leads the Robot Control and Learning Group at the Sun Yat-sen University, Guangzhou, China. He holds the Ph.D. degree in control theory and control engineering from the South China University of Technology, Guangzhou, and has long-term research experience in top universities worldwide. His research interests include automatic control and machine learning with applications to robotics such as compliant actuation, interaction control, visual servoing, motion planning, and dexterous manipulation. Based on his research, Dr. Pan has authored or co-authored more than 120 peer-reviewed academic papers, including about 100 papers in refereed journals, where his publications have attracted over 5000 and 3800 citations in Google Scholar and Web of Science Core Collection, respectively. He has been invited as an Associate Editor of several top-tier journals, such as IEEE-TCSE, IEEE-TASE, and IEEE-CAL, and as a speaker to deliver academic talks in top universities and conferences over 30 times worldwide. He was selected as a Clarivate global Highly Cited Researcher.


Speech Title: Composite Learning Tracking and Interaction Control for Compliant Robots

Abstract: Due to the rapid population aging globally, the current trend of robotic research has been shifting from traditional industrial robots that are separated from humans to human-centered robots that coexist, cooperate, and collaborate with humans. A major motivation for introducing compliance to human-centered robots is physical human-robot interaction. This talk considers compliant robots with flexible joints and highlights our major results in composite learning control for compliant robots. First, we establish the connection of the human motor learning and control mechanism to adaptive and learning control theory. Second, we propose a composite learning methodology to achieve efficient learning from the bioinspired adaptive robot control. Third, we apply composite learning control methods to improve the accuracy, safety, and naturalness of compliant robots. Experiments based on several physical robots are provided to verify the proposed methods.

Prof. Zheng WANG

Southern University of Science and Technology, China


BIO:Dr Zheng WANG graduated from Tsinghua University, China (BEng), Imperial College, UK (MSc), Technical University of Munich, Germany (D-Ing), and served as Postdoc Fellow in Nanyang Technological University and Harvard University, respectively. From 2014-2019 he served as Assistant Professor in the Department of Mechanical Engineering at the University of Hong Kong, before joining SUSTECH in 2019 as Professor and Principal Investigator. Dr Wang’s research interests include: Soft robotic design and control, compliant mechanism modeling and analysis, flexible & bionic design and fabrication, and extreme environment (medical / underwater / energy) robotic systems. He had successfully led and collaborated in over 20 research grants across EU, Singapore, US, HK, and China, receiving sponsorship from HK RGC, ITC, Shenzhen Technological and Innovation Committee, and major leading companies from Microsoft, Delta, Lenovo, MBrain, Hytera, Tencent, etc. Dr Wang is currently a Senior Member of IEEE and IEEE RAS, and Member of ASME, TE for IEEE/ASME TMECH, AE for IMechE JSCE and Machines, and reviewing panelist for Nature, Science, Nat Comm, Sci. Rob, and EU/Singapore/HK/NSFC grant councils. To-date Dr Wang had authored nearly 100 academically refereed articles (GS citation 3000+, H-Index=27), and over 30 patents.


个人简介:王峥,毕业于清华大学,分获英国帝国理工大学、德国慕尼黑工业大学硕士、博士学位,并先后于新加坡南洋理工大学机器人研究院和美国哈佛大学WYSS仿生工程研究院任博士后研究员。2014-2019年于香港大学机械工程系担任助理教授。2019年加入南科大担任教授,博士生导师。研究兴趣和方向包括:柔性机器人设计与控制,柔性机构建模与力学仿真分析,柔性仿生设计与精密加工,及特种环境(医疗/水下/能源)机器人系统。先后主持和参与欧盟、新加坡、美国、香港和内地的科研项目20余项,得到香港科技署、香港创新科技署、深圳科创委和知名企业的资助。现任IEEE和IEEE RAS高级会员,ASME会员,IEEE/ASME TMECH技术编辑,IMechE JSCE副主编,Machines副主编,并为Nature,Science,Nat Comm,Sci-Rob等期刊和欧盟、新加坡、香港、基金委担任评审专家。迄今共发表学术论文近百篇(GS引用3000+,H-Index=27),专利30余项。