Academic Report:Modeling, Sensing and Control of Unstable Physical Human-Machine Interactions: A Rider-Bicycle Example

Provenance:流体动力与机电系统国家重点实验室英文网Release time:2015-04-02Viewed:2


Academic ReportModeling, Sensing and Control of Unstable Physical Human-Machine Interactions: A Rider-Bicycle Example



SpeakerProfessor Jingang Yi Department of Mechanical and Aerospace EngineeringRutgers University, Piscataway, NJ 08854, USA

Time2014.07.3010:00AM

LocationConference Room, 4th Floor, Hydraulic Old Building, Yuquan Campus


Abstract:

    Human with trained motor skills can fluidly and flexibly interact with machines while smart machines can also provide motor assistance and enhancement to facilitate human’s motor skills learning. However, we currently lack theories and design tools to effectively model and tune human motor control and its interactions with machines. In this talk, I will discuss recent developments at Rutgers Robotics, Automation and Mechatronics (RAM) Lab on modeling, sensing and control of human motor skills through unstable physical human-machine interactions (upHMI). Rider-bicycle interactions is used as an upHMI paradigm to examine a sensorimotor theory for modeling and shaping human motor control relevant to balancing and other functional whole-body motor activities. I will first present a novel control-theoretic physical/statistical modeling framework of extracting and characterizing human motor control strategies in a lower-dimensional space. Then, I will discuss the development of the in-situ sensing and actuation design to estimate the poses of the rider and the bicycle in natural environment with wearable and onboard sensors and actuators. Finally, I will present balancing control design and neuro-controller stability analysis for the rider-bicycle interactions. If time permits, I will also briefly describe various other robotic research projects at the RAM Lab in the end of the talk.


Brief Bio:

    Prof. Jingang Yi received the B.S. degree in electrical engineering from Zhejiang University, China in 1993, the M.Eng. degree in precision instruments from Tsinghua University, China in 1996, the M.A. degree in mathematics, and the Ph.D. degree in mechanical engineering from the University of California, Berkeley, in 2001 and 2002, respectively. Currently, Dr. Yi is an Associate Professor in mechanical engineering and also a graduate faculty member in electrical and computer engineering at Rutgers University. His research interests include autonomous robotic systems, mechatronics, dynamic systems and control, automation science and engineering, with applications to biomedical systems, civil infrastructure and transportation systems and semiconductor manufacturing. Dr. Yi has received many prestigious awards, including the 2014 ASCE Charles Pankow Award for Innovation, the 2013 Rutgers Board of Trustees Research Fellowship for Scholarly Excellence, and the 2010 US NSF CAREER Award, etc. He has also co-authored papers that have been awarded the Best Student Papers at the 2012 ASME Dynamic Systems and Control Conference and 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics and the Kayamori Best Paper at the 2005 IEEE International Conference on Robotics and Automation. Dr. Yi is a member of American Society of Mechanical Engineers (ASME) and a senior member of the IEEE. He serves as an Associate Editor of the IEEE Transactions on Automation Science and Engineering, IFAC Journal Control Engineering Practice, the ASME Journal of Dynamic Systems, Measurement and Control, and the IEEE Robotics and Automation Society (RAS) Conference Editorial Board (since 2008). He also served as a Guest Editor of IEEE Transactions on Automation Science and Engineering in 2009 and an Associate Editor of the ASME Dynamic Systems and Control Division Conference Editorial Board from 2008 to 2010.