Institute of Robotics and Automatic Information System Tianjin Key Laboratory of Intelligent Robotics
Seminar Series：Advanced Robotics & MEMS
题目：Physical Field Perception for Robotics, Automation and Mechatronics (RAM)
报告人：Kok-Meng Lee ASME Fellow, IEEE Fellow
Professor, Georgia Institute of Technology, Atlanta, GA
Past Editor-in Chief (前主编), IEEE/ASME Transactions on Mechatronics
Abstract: As compared to a human visual system (HVS) which is incredibly adapted to seeing “optical fields” in a 3D world and applying lifelong learning/training as constraints to deal with ambiguous situations, such levels of sophistication are difficult to emulate on a machine vision system (MVS) particularly for solving human life applications. On the other hand, machines that creatively utilize one or more physical fields perform far better than human in engineering applications where process monitoring and products quality control are measured quantitatively. Recent advances in 3C (computing, communication and control) technologies and experimental techniques, coupled with dramatic reductions in cost, have enabled the ability to generate massive raw data, turn them into physical-field perception (information), then into 4D engineering models (knowledge). In principle, it is possible to create intelligent machines capable of learning equal (or better) than human. However, in order to do so, it is necessary to take into account some fundamental differences between qualitative human-based and quantitative engineering data. This talk presents several new techniques to overcome limitations in traditional approaches with selected application examples which help illustrate the impacts and yet to cover a wide variety of RAM applications. The intended audience of this talk includes undergraduates, graduate students and faculty with engineering backgrounds.
Dr. Kok-Meng Lee (firstname.lastname@example.org) 于1980年在纽约州立大学取得学士学位，于1982年和1985年在麻省理工学院分别获得硕士和博士学位。
李博士是ASME Fellow, IEEE Fellow. 现任 Division Chair of ASME Dynamics Systems and Control。他的研究成果得到广泛认可，获得了多个奖项，包括the National Science Foundation (NSF) Presidential Young Investigator, Sigma Xi Junior Faculty Research, International Hall of Fame New Technology, Kayamori Best Automation Paper and IEEE/ASME Transactions on Mechratonics Best Paper awards.