Oct 8th (Monday）
Mutli-Scale Robotic System
– From brachiation robot to micro/nano robotic manipulation –
This lecture is an overview of the Multi-scale robotics, based on the Cellular Robotics System, which is the basic concept of the emergence of intelligence in the multi-scale way from Cell Level to the Organizational Level, proposed more than 30 years ago. It consists of many elements how the system can be structured from the individual to the group/society levels in analogy with the biological system. It covers with the wide range of challenging topics:
- Distributed autonomous robotic system
- Individual robot level, Brachiation Robots and Multi-locomotion robots,
- Care Service robots
- Medical robotics and simulator,
- Micro and nano robotics system
- Bio analysis and bio-synthesis: bio-robotics system
- Cyborg and Bionic System
- Other systems.
Then I mainly focus on bio cell manipulation and cell assembly and refer to applied areas for the future hybrid system to improve the quality of life of human.
Beijing Institute of Technology
Toshio Fukuda graduated from Waseda University, Tokyo, Japan in 1971 and received the Master of Engineering degree and the Doctor of Engineering degree both from the University of Tokyo, in 1973 and 1977, respectively. He joined the National Mechanical Engineering Laboratory in Japan in 1977, the Science University of Tokyo in 1982, and then joined Department of Mechanical Engineering, Nagoya University, Japan in 1989. He worked at University of Stuttgart, as Humboldt Fellow in 1979-1981.
He is currently one thousand talented foreign Professor at BIT. He is Professor Emeritus of Nagoya University. Department of Micro and Nano-Systems Engineering and Professor of Meijo University. He has been working as Professor of Shenyang University of Technology, Suzhou University, Institute of Automation, Chinese Academy of Science, Russell Springer Chaired Professor at UC Berkeley, Seoul National University, Advisory Professor of Industrial Technological Research Institute in Taiwan and etc.
He is mainly engaging in the research fields of intelligent robotic system, micro and nano robotics, bio-robotic system, and technical diagnosis and error recovery system.
He was the President of IEEE Robotics and Automation Society (1998-1999), Director of the IEEE Division X, Systems and Control (2001-2002), the Founding President of IEEE Nanotechnology Council (2002-2005), Region 10 Director (2013-2014) and Director of Division X, Systems and Control (2017-2018). He was Editor-in-Chief of IEEE/ASME Trans. Mechatronics (2000-2002).
He was the Founding General Chair of IEEE International Conference on Intelligent Robots and Systems (IROS) held in Tokyo (1988). He was Founding Chair of the IEEE Workshop on Advanced Robotics Technology and Social Impacts (ARSO, 2005), Founding Chair of the IEEE Workshop on System Integration International (SII, 2008), Founding Chair of the International Symposium on Micro-Nano Mechatronics and Human Science (MHS, 1990-2012).
He has received many awards such as IEEE Eugene Mittelmann Achievement Award (1997), IEEE Third Millennium Medal (2000) , Humboldt Research Prize (2003), IEEE Robotics and Automation Pioneer Award (2004), IEEE Transaction Automation Science and Engineering Googol Best New Application Paper Award (2007), George Saridis Leadership Award in Robotics and Automation (2009), IEEE Robotics and Automation Technical Field Award (2010). He received the IROS Harashima Award for Innovative Technologies (2011), Friendship Award of Liaoning Province PR China (2012), Friendship Award from Chinese Government (2014), JSME Achievement Award (2015), IROS Distinguished Service Award (2015) and Honor of Medal with the Purple Ribbon from Japanese Government (2015). Award from Automation Foundation (2016).
IEEE Fellow (1995). SICE Fellow (1995). JSME Fellow (2002), RSJ Fellow (2004), VRSJ Fellow (2011) and member of Science Council of Japan (2008-2014 ), Academy of Engineering of Japan (2013-), and Foreign member of Chinese Academy of Science (2017).
Oct 9th (Tuesday)
Cyber-Physical & Human Systems:
New Horizons in Transportation and Energy Infrastructures
The Cyber-Physical Systems (CPS) framework has enabled multidisciplinary research that combines physics-based tools related to modeling, estimation, control, and automation, with cyber-centric tools of communications, sensing, networking, and computing. This has led to new research directions consisting of both new theoretical tools and new technological applications in various sectors, including transportation, energy, healthcare, manufacturing, and robotics. A common ingredient in these research directions is the interaction of humans with CPS, precipitating the new entity, Cyber-physical & Human Systems (CPHS). Different types of CPHS are emerging of late, depending on the type of interactions. These interactions can be for various purposes, and lead to various challenges. For example, a human-in-the-loop interaction occurs where humans are empowered consumers/customers so as to lead to an efficient infrastructure. A human-on-the-loop interaction may occur in cases where humans correspond to skilled operators and can provide high-level oversight and supervision for the CPS. Such CPHS are emerging in both the energy and transportation infrastructures, where examples of the first kind are (1) Smart Grids with Demand Response and (2) Urban Mobility with Ride-Sharing, and those of the second kind are (3) Flight Control using Shared Decision-making between pilots and autopilots.
This talk will focus on CPHS in energy and transportation infrastructures, with particular focus on the above three examples. The analysis and synthesis of such CPHS will be described with emphasis on how tools such as prospect theory and Transactive control that help in modeling behavioral dynamics of humans as well as concepts from cognitive modeling of human behavior in extreme events such as Capacity for Maneuver and Graceful Command Degradation can be combined with well known system-theoretic tenets of physics-based modeling, system identification, adaptive control, and optimization. Case studies that illustrate the behavior of each of the above three examples will be presented exemplifying how efficient CPHS can be designed.
Active-adaptive Control Laboratory
Massachusetts Institute of Technology
Dr. Anuradha Annaswamy is a Senior Research Scientist in the Department of Mechanical Engineering and the Director of Active-adaptive Control Laboratory at MIT. She received her Ph.D. in Electrical Engineering from Yale University in 1985. She has been a member of the faculty at Yale (1988), Boston University (1988-91), and MIT (1991 – present). Her research interests pertain to adaptive control theory and applications to aerospace, automotive, and propulsion systems, cyber physical systems science, and CPS applications to Smart Grids, Smart Cities, and Smart Infrastructures. She is the author of over a hundred journal publications and numerous conference publications, co-author of a graduate textbook on adaptive control (2004) and co-editor of several vision documents including “Systems & Control for the future of humanity, research agenda: Current and future roles, impact and grand challenges,” (Elsevier) “IEEE Vision for Smart Grid Control: 2030 and Beyond,” (IEEE Xplore) and Impact of Control Technology, (ieeecss.org/main/IoCT-report, ieeecss.org/general/IoCT2-report).
Dr. Annaswamy has received several awards including the George Axelby and Control Systems Magazine best paper awards from the IEEE Control Systems Society (CSS), the Presidential Young Investigator award from NSF, the Hans Fisher Senior Fellowship from the Institute for Advanced Study at the Technische Universität München, the Donald Groen Julius Prize from the Institute of Mechanical Engineers, a Distinguished Member Award, and a Distinguished Lecturer Award from IEEE CSS. Dr. Annaswamy is a Fellow of the IEEE and IFAC. She has served as the Vice President for Conference Activities (2014-15), and is currently serving as the VP for Technical Activities (2017-18) in the Executive Committee of the IEEE CSS.
Oct 10th (Wednesday)
Novel Discriminative and Generative Learning Algorithms:
Broad Learning System and Fuzzy Restricted Boltzmann Machines
C. L. Philip Chen
In recent years, deep learning caves out a research wave in machine learning. With its outstanding performance, more and more applications of deep learning in pattern recognition, image recognition, speech recognition, and video processing have been developed. This talk is to discuss a very fast and efficient discriminative learning –- “Broad Learning System”. Without stacking the layer-structure, the designed neural networks expand the neural nodes broadly and update the weights of the neural networks incrementally when additional nodes are needed and when the input data entering to the neural networks continuously. The designed network structure and learning algorithm are perfectly suitable for modeling and learning big data environment. Several experiments results are presented. The second part of the talk is to introduce a fuzzy generative learning algorithm, Fuzzy Restricted Boltzmann Machine (FRBM). The FRBM as its variants are developed by replacing real-valued weights and bias terms with symmetric, non-symmetric triangular fuzzy numbers (STFNs) or Gaussian fuzzy numbers and corresponding learning algorithms. Experiments indicates that the FRBM significantly improves learning accuracy and generalization ability, especially when it encounters unlearned and noisy samples.
C. L. Philip Chen
University of Macau
Dr. Chen’s research areas are in systems, cybernetics and computational intelligence. He is a Fellow of the IEEE, AAAS, and IAPR. He was the President of IEEE Systems, Man, and Cybernetics Society (SMCS) (2012-2013), where he also has been a distinguished lecturer for many years and received Outstanding Service Awards 4 times. Currently, he is the Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014-). He has been an Associate Editor of several IEEE Transactions, and currently he is an Associate Editor of IEEE Trans on Fuzzy Systems, IEEE Trans on Cybernetics, and IEEE/CAA Automatica Sinica. He was the Chair of TC 9.1 Economic and Business Systems of IFAC (2015-2017). He is also a Fellow of CAA and Fellow of HKIE and an Academician of International Academy of Systems and Cybernetics Science (IASCYS). In March 2018, he is listed in world top 14 having the most highly cited paper in computer science area by WoS. In addition, he is an ABET (Accreditation Board of Engineering and Technology Education, USA) Program Evaluator for Computer, Electrical, and Software Engineering programs. University of Macau’s Engineering and Computer Science programs receiving HKIE’s accreditation and Washington/Seoul Accord is his utmost contribution in engineering education for Macau as the former Dean. During his deanship, the engineering and computer science programs both have been ranked at world top 200 in the Times Higher Education (THE) world university ranking. The computer science program is also ranked at world top 161 in the US News and World Report global university ranking. Dr. Chen received Outstanding Electrical and Computer Engineering Award in 2016 from his alma mater, Purdue University, West Lafayette, where he received his Ph.D. degree in 1988, after he received his M.S. degree in electrical engineering from the University of Michigan, Ann Arbor, in 1985.