Max Meng, FIEEE, Distinguished Chair Professor at Harbin Institute of Technology, Distinguished Provincial Professor at Henan University of Science and Technology, China
Title: Robotics to Facilitate Robots to Merge into Society
Abstract: Intelligence and perception represent the benchmark capability of the new generations of intelligent robots and are missing from the mechanically capable modern robots. Research on robotic intelligence and perception is not new and many waves of research efforts have come and gone since the rise of the modern perception and psychophysics in early 20th century and the AI in mid 20th century. Recent revolutionary development and progress in information technology in terms of both hardware capability and software power have made it possible for researchers to redefine what robotic perception and intelligence are and rethink how research on the topics can take full advantage of the current information technology accomplishments. In this talk, we will start with an introduction to how research on perception and AI started and what the milestone achievements are, and then move onto topics from classic psychophysics and sensory substitution to modern concepts of multi-sensory information fusion, soft-haptics and active perception. Intuitive examples and application scenarios will be presented to illustrate key points and important concepts. Personal thoughts and projections on future research efforts and potentials in perception and AI will be outlined to conclude the talk.
Short Bio: Max Q.-H. Meng received his Ph.D. degree in Electrical and Computer Engineering from the University of Victoria, Canada, in 1992, following his Master's degree from Beijing Institute of Technology in 1988. He has been a Professor of Electronic Engineering at the Chinese University of Hong Kong since 2002, after working for 10 years in the Department of Electrical and Computer Engineering at the University of Alberta in Canada as the Director of the ART (Advanced Robotics and Teleoperation) Lab, holding the positions of Assistant Professor (1994), Associate Professor (1998), and Professor (2000), respectively. He was jointly appointed as an overseas outstanding scholar chair professor of the Chinese Academy of Sciences and the Dean of the School of Control Science and Engineering at Shandong University in China. He is currently jointly appointed as a distinguished chair professor at HIT, a distinguished provincial professor of Henan University of Science and Technology, and the honorary dean of the School of Control Science and Engineering at Shandong University, in China. His research interests include robotics, robotic perception and intelligence, robotic medical devices, bio-sensors and sensor networks, network enabled systems and services, and adaptive and intelligent systems. He has published more than 500 journal and conference papers and book chapters and led more than 40 funded research projects to completion as Principal Investigator. He has served as an editor of the IEEE/ASME Transactions on Mechatronics and an associate editor of the IEEE Transactions on Fuzzy Systems, and is currently a technical editor of Advanced Robotics, Journal of Robotics and Biomimetics, Journal of Advanced Computational Intelligence and Intelligent Informatics, and International Journal of Information Acquisition, as well as the honorary editor-in-chief of the International Journal of Automation and Logistics. He was the General Chair of IEEE CIRA 2001, IROS 2005, AIM 2008, and WCICA 2010 conferences, and many others. He served as an Associate VP for Conferences of the IEEE Robotics and Automation Society (2004-2007), an AdCom member of the IEEE Neural Network Council/Society (2003-2006), a member of the IEEE/ASME Transactions on Mechatronics Management Committee (2001-2006), and the Co-Chair of the Fellow Evaluation Committee of the IEEE Robotics and Automation Society. He is currently serving as a member of the Administrative Committee (AdCom) of the IEEE Robotics and Automation Society. He is a recipient of the IEEE Third Millennium Medal award and a Fellow of IEEE.
Prof. Clarence W. de Silva, FIEEE, FCAE, FRSC, FASME, Professor and Senior Canada Research Chair in Mechatronics and Industrial Automation, University of British Columbia, Canada
Title: Some Issues and Applications of Multi-robot Cooperation
Abstract: There are many applications of multi-robot cooperation. They include factory floor, emergency response and rescue, homecare, natural resource monitoring, and outdoor industrial operations such as fault diagnosis and repair. This talk will address several relevant issues in such applications of cooperative robotics, particularly: sensing and instrumentation, control, and networked operation. Two specific domains of application will be given primary focus. They are outdoor emergency response and homecare robotics.
In one application, a cooperative multi-robot system provides emergency services such as clearance, cleanup and human rescue in a disaster situation in an urban environment. In this application it is assumed that the available robots are heterogeneous with different types and levels of resources and capabilities and are not specifically designed for the emergency application. The robots will have their regular tasks for which they are designed (e.g., trash clearing, traffic control, providing assistance to the elderly and the disabled, surveillance, environmental monitoring, fault diagnosis and repair of a material distribution network). Also it is assumed that there is a means for communicating with robots from any location (e.g., wireless sensor network). When called upon to carry out an emergency operation, the available robots in the neighborhood will quickly navigate to the site and will negotiate the necessary tasks based on the needs, the robot capabilities, and the available material and other resources. Then they will carry out cooperative tasks to provide appropriate assistance (e.g., construction of a carriage or cart, rescuing humans, providing first aid).
The second application concerns homecare robotics. This may involve autonomous robots that provide basic and routine assistance to the elderly and the disabled in a home setting (e.g., serving food and medicine, cleaning, bathing, and aiding mobility); and bilateral teleoperation of a robot from a hospital control room to provide professional assistance (e.g., first aid) while the traditional emergency help is forthcoming. The vast majority of the elderly and the disabled prefer to maintain independent households. A significant fraction of the public cost for supporting the disabled and the elderly goes into homecare and related expenses. In this context, the benefits of homecare robotics are tremendous. In particular, the quality of life of the elderly and the disabled will improve, allowing them more flexibility and comfort, in the presence of round-the-clock and reliable care. Also, other members of the household will have increased freedom and peace of mind to pursue their normal activities including employment and education. Furthermore, the related public spending will be more uniform, fair, and cost effective. In the application scenario, one or more robots will be available with their local sensors and a range of networked global sensors in the home environment. Adequate robotic intelligence is crucial for autonomous operation while haptic feedback is important in teleoperation. Sensory, mobility, grasping, manipulation, and control capabilities are needed for both categories of operation. The needed basic technologies of robotics, networked communication, control, and teleoperation are sufficiently mature and are available at reasonable cost. Further development is needed in assistive technologies, specialized end-effector devices, and haptics.
The talk will particularly highlight key technologies of sensing, instrumentation, object identification and localization, detection and evaluation of abnormal motions in humans, robotic navigation in the presence of static and dynamic obstacles, grasping and manipulation, networked intelligent sensor fusion and feedback, impedance control in haptic teleoperation, and stable operation, which are pertinent in both application domains. An integrated intelligent approach may be used for the coordinated operation and control of a multi-robot system. In particular, a common system architecture with optimally self-adaptive, intelligent, and dynamic agent network may be implemented for multiple engineering applications. This is an innovative paradigm. The operation of the networked multi-robot system may be optimized by sharing resources among the applications. Dynamic/mobile sensors will receive "feedback" from themselves, to improve their sensing effectiveness (e.g., data/information quality, relevance of their data, speed, confidence). The networked agents will possess some degree of "intelligence" to facilitate autonomous operation and to achieve the desired performance. The system will be able to predict, detect, and diagnose malfunctions and faults in it and accommodate or self-repair them.
Short Bio: Clarence W. de Silva is a Professor of Mechanical Engineering and occupies the Senior Canada Research Chair Professorship in Mechatronics & Industrial Automation at the University of British Columbia (UBC), Vancouver, Canada. A Professional Engineer (P.Eng.), he is also a Fellow of: ASME, IEEE, Canadian Academy of Engineering, and the Royal Society of Canada. He is a Peter Wall Scholar at UBC; a Professorial Fellow at University of Melbourne; Distinguished Visiting Fellow of the Royal Academy of Engineering, UK; Lilly Fellow at Carnegie Mellon University; NASA-ASEE Fellow; Senior Fulbright Fellow to Cambridge University; Fellow of the Advanced Systems Institute of BC; Killam Fellow; and Erskine Fellow at University of Canterbury. He has held NSERC-BC Packers Senior Chair Professorship at UBC; Mobil Endowed Chair Professorship at National University of Singapore; Honorary Chair Professorship at National Taiwan University of Science and Technology; and Honorary Professorship at Xiamen University, China. His awards include the Paynter Outstanding Investigator Award and the Takahashi Education Award of ASME; Killam Research Prize; and Outstanding Engineering Educator Award of IEEE Canada. He has served as Editor/Associate Editor of 14 journals including ASME and IEEE transactions; and is the Editor-in-Chief of the International Journal of Control and Intelligent Systems. His publications include 22 authored books, 19 edited books, 238 journal papers, and 263 conference papers. He has Ph.D. degrees from Massachusetts Institute of Technology, USA (1978) and the University of Cambridge, UK (1998), and an Honorary D.Eng. from the University of Waterloo (2008).
Prof. C. L. Philip Chen, FIEEE, FAAAS, Dean and Chair Professor, Faculty of Science and Technology, The University of Macau
Title: Big Data Challenges, Techniques, Technologies, and Applications and How Deep Learning can be Used
Abstract: It is already true that Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. A large number of fields and sectors, ranging from economic and business activities to public administration, from national security to scientific researches in many areas, involve with Big Data problems. This talk is aimed to demonstrate a close-up view about Big Data, including Big Data applications, Big Data opportunities and challenges, as well as the state-of-the-art techniques and technologies that we currently adopt to deal with the Big Data problems. The second part is to discuss the deep learning role in Big Data. In recent years, deep learning caves out a research wave in machine learning. With outstanding performance, more and more applications of deep learning in pattern recognition, image recognition, speech recognition, and video processing have been developed. Restricted Boltzmann machine (RBM) plays an important role in current deep learning techniques, as most of existing deep networks are based on or related to it. This talk will also discuss how the big data relates with the deep learning.
Short Bio: C. L. Philip Chen (S'88,M'88,SM'94,F'07) received his M.S. degree in electrical engineering from the University of Michigan, Ann Arbor, in 1985 and the Ph.D. degree in electrical engineering from Purdue University, West Lafayette, IN, in 1988. After having worked at U.S. for 23 years as a tenured professor, as a department head and associate dean in two different universities, he is currently the Dean of the Faculty of Science and Technology, University of Macau, Macau, China and a Chair Professor of the Department of Computer and Information Science. Dr. Chen is a Fellow of the IEEE and AAAS. He was the President of IEEE Systems, Man, and Cybernetics Society (SMCS) (2012-2013). Currently, he is the Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014-). Having been an Associate Editor of many IEEE Transactions, he is currently an Associate Editor of IEEE Trans on Fuzzy Systems, IEEE Trans on Cybernetics, IEEE/CAA Automatica Sinica, and several IEEE Transactions. He is also the Chair of TC 9.1 Economic and Business Systems of IFAC. His research areas are systems, cybernetics, and computational intelligence. He is also an executive board member of SMCS and Chinese Association of Automation (CAA), Associate Editor-in-Chief of Communications of CAA, Fellow of CAA and Fellow of HKIE. In addition, he is an ABET (Accreditation Board of Engineering and Technology Education) Program Evaluator for Computer Engineering, Electrical Engineering, and Software Engineering programs.