October 12(Tue)~15(Fri), 2021
Ramada Plaza Hotel, Jeju

Invited Speakers

Invited Speakers

Distributed Optimal Traffic Control: Modeling and Synthesis

Prof. Hyo-Sung Ahn
GIST, Korea

Motivated by the fact that intelligent traffic control systems have become inevitable, and to cope with the risk of traffic congestion in urban areas, a novel distributed control strategy for urban traffic networks is developed. Since these networks contain a large number of roads having different directions, each of them can be described as a multi-agent system. Thus, a coordination among traffic flows is required to optimize the operation of the overall network. In order to determine control decisions, we describe the objective of improving traffic conditions as a constrained optimization problem with respect to downstream traffic flows. By applying the gradient projection method and the minimal polynomial of a matrix pair, we propose algorithms that allow each road cell to determine its control decision corresponding to the optimal solution while using only its local information.

Hyo-Sung Ahn received the B.S. and M.S. degrees in astronomy from Yonsei University, Seoul, Korea, in 1998 and 2000, respectively, the M.S. degree in electrical engineering from the University of North Dakota, Grand Forks, in 2003, and the Ph.D. degree in electrical engineering from Utah State University, Logan, UT, USA, in 2006. He is currently a Professor at the School of Mechanical Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea. Since July 2007, he has been with the School of Mechatronics and School of Mechanical Engineering, GIST. He was Dasan Distinguished Professor (Dasan Professor) from 2013 to 2018. Before joining GIST, he was a Senior Researcher at ETRI, Daejeon, South Korea. He was a visiting scholar at Colorado School of Mines in 2019. He is serving as an Editor at SICE Journal of Control, Measurement, and System Integration (JCMSI) and Int. Journal of Control, Automation & Systems. His research interests include distributed control, aerospace navigation and control, network localization, and learning control. He is the author of the books “Iterative learning control: Robustness and Monotonic Convergence for Interval Systems,” Springer, 2007, and “Formation Control – Approaches for Distributed Agents,” Springer, 2020.

Wearable Robots in Reality

Prof. Kyoungchul Kong
KAIST, Korea

Robotics technologies are steadily penetrating in our daily lives. We are surrounded by robotic products and interact with them in many ways. Such systems may potentially improve the quality of life of people with major or minor impairments in walking ability. Since the Iron Man movie became popular, many people are looking forward to wearable robots in reality as a means of assistance device for the elderly, patients, and anyone with physically demanding works. By the help of recent remarkable advancement of key technologies, a wearable robot is no longer a hero in a science-fiction movie. The powered exoskeleton race of the Cybathlon 2020 showed several wearable robots, where two pilots of KAIST team received the Gold and Bronze medals respectively, and the speed of the Gold medalist wearing a powered exoskeleton was faster than most of the powered wheel-chairs. In addition, wearable robots for rehabilitation purposes have been commercialized by many companies all over the world, and anyone with difficulty in walking can experience wearable robots in near rehabilitation centers. In this talk, several key technologies recently advanced for wearable robots are introduced. These technologies include 1) sensing technologies for observing the dynamic state of the human wearing a robot, as well as for identifying the intent of humans, 2) decision making algorithms to decide about the right amount of assistance, 3) actuation technologies to provide precise assistive forces, and 4) control algorithms for providing assistance as needed. Based on these key technologies, success stories of WalkON Suit, the Gold medalist of the powered exoskeleton race of Cybathlon 2020, and Angel Legs, a commercialized wearable robot for rehabilitation purposes, will be introduced in this talk also.

Kyoungchul Kong received the B.Eng. degree (summa cum laude) in mechanical engineering, the B.S. degree in physics in 2004, and the M.S. degree in mechanical engineering in 2006 from Sogang University, Seoul, Korea, and the Ph.D. degree in mechanical engineering from the University of California at Berkeley, CA, USA, in 2009, where he later became a Postdoctoral Research Fellow until 2011.

In 2011, he joined the Department of Mechanical Engineering, Sogang University, as an assistant professor. He is currently an associate professor of the Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST). He is a founder and the CEO of Angel Robotics, a start-up company for productizing wearable robots.

Dr. Kong received the Best Innovation Award from the President of South Korea in 2017, the Commendation by the Minister of Commerce, Industry and Energy in 2017, the Bronze Medal of Cybathlon 2016, the Young Researcher Award of IFAC Mechatronics TC in 2016, the Gold Medal and Bronze Medal of Cybathlon 2020, and many others.

Control Issues on Bipedal Walking Robots

Prof. Jaeheung Park
Seoul National University, Korea

Recently four legged robots are becoming quite robust and, therefore, can have many promising applications such as industrial surveillance.
Two legged robots also have great progress toward more robust walking.
However, two legged robots have an inherent stability problem due to the fact that it has only two feet. In this talk, I would like to explain the unique characteristics of two legged robots in terms of hardware and control. Two legged robots require the feet of a finite size to stand still, but these feet make the dynamic characteristics of the robot difficult to control. On the other hand, the feet are always making contacts while walking. It is challenging to deal with this continuous contact in terms of sensing and control. Among many possible approaches, some of the methods that our research group is pursuing will be also introduced in these aspects.Jaeheung Park is a Professor in the Department of Intelligence and Information at Seoul National University, South Korea, since 2009.

Prior to joining Seoul National University, he shortly worked at Hansen Medical Inc, a medical robotics company. He received a Ph.D. degree from Stanford University, and the B.S. and M.S. degrees from Seoul National University. His research group is currently conducting many national projects on the topics of humanoid robots, rehabilitation/medical robots, and autonomous vehicles. He was a team leader of TEAM SNU for DRC Finals 2015 (DARPA Robotics Challenge Finals), which was a robotics competition for disaster response. In 2016, His team won the award given by Minister of Science, ICT, and Future Planning, at Challenge Parade that was held by the Korean Government. He has participated in organizing many international robotics conferences such as IROS, HUMANOIDS, and HRI. He has also served as a Conference Editorial Board or as an Associate Editor for many international conferences. He currently serves as a co-chair of the RAS Technical Committee on Whole-body Control.

Autonomy and interaction capabilities of robots in performing complex tasks

Prof. Ivan Petrović
University of Zagreb, Croatia

The main robotics challenges in the next few decades will be to develop autonomous robotic systems that can perform complex tasks in human environments and safely cooperate with humans in arbitrary settings. Robots with these capabilities will transform our everyday lives and industrial processes with a significant impact on life, business, and the global economy. The talk will feature recent research activities and achievements of my Lab with emphasis given on our recently developed algorithms for sensor fusion, localization and mapping, motion planning, and human intention recognition. For all algorithms, I will present experimental results that have been obtained in real-world environments. I will conclude the talk with a brief discussion on open research challenges and potential directions for future research.

Ivan Petrović is a full professor at the Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia, where he directs the Laboratory for Autonomous Systems and Mobile Robotics – LAMOR (http://lamor.fer.hr). He is also the co-director of the Centre of Research Excellence for Data Science and Advanced Cooperative Systems (https://across-datascience.zci.hr/en/zci). In the research work, he addressed various aspects of automatic control, state estimation, and machine learning and their application in control of complex technical systems, where the autonomy of mobile robots and vehicles and human-robot interaction have been in his research focus for the last twenty years. He published his research achievements as an author or co-author of more than 70 papers in scientific journals and more than 200 papers in proceedings of international conferences. He has actively participated as a collaborator or principal investigator in more than 60 research and development projects at the national and EU levels. Results of his research effort have been implemented in several industrial products. He is an active member of national and international professional societies. Among others, he is a full member of the Croatian Academy of Engineering, chair of the Technical Committee on Robotics of the International Federation of Automatic Control (IFAC), and a permanent board member of the European Conference on Mobile Robots. He is Editor-in-Chief of the Automatika journal and Associate Editor of the Mechatronics journal.

Dynamics for Robot Control and Simulation

Prof. Subir Kumar Saha
IIT Delhi, India

In this talk, the speaker will introduce the concept of DeNOC matrices for the efficient modeling of robot manipulators with a lot of physical interpretations. It is an evolution of last 25 years. The methodology yields recursive order (n) algorithms which at times are needed for real-time control and simulation. The talk will be illustrated with examples, and how two robot simulation software, namely, RoboAnalyzer and ReDySim, were developed.

Prof. Subir Kumar Saha, a 1983 Mechanical Engineering graduate from RE College (Now NIT), Durgapur, India, completed his M. Tech from IIT Kharagpur, India, and Ph. D from McGill University, Canada. Upon completion of his Ph. D, he joined Toshiba Corporation’s R&D Center in Japan. After 4-years of work experience in Japan, he has been with IIT Delhi since 1996.

Prof. Saha is a professor in the Department of Mechanical Engineering at IIT Delhi, and the Project Director of the USD20.0 million non-profit company I-Hub Foundation for Cobotics incorporated in June 2021 with the funding from the DST (Govt. of India) at IIT Delhi. Recently, he was awarded with the 2020 Distinguished Alumnus Award in Research and Development by NIT Durgapur. Prof. Saha was Humboldt Fellows during 1999-2000 at the Univ. of Stuttgart, Germany, and the Naren Gupta Chair Professorship at IIT Delhi during 2010-20. He has been also a visiting faculty at IIT Madras and short term researcher at Mcgill University, Canada, Monash University, Australia, and University of Verona, Italy. Prof. Saha’s text book on “Introduction to Robotics” published by McGraw-Hill in India and Singapore was also translated in Mexican Spanish. To make learning the subject of robotics fun, a software called RoboAnalyzer was developed under his supervision and distributed free through www.roboanalyzer.com. He has co-authored two more specialized books with two of his ex-Ph. D students, 1) “Dynamics of Tree-type Robotics Systems” supported with ReDySim (Recursive Dynamics Simulator) software; and 2) “Dynamics and Balancing of Multibody Systems.” Both were published by Springer. He has more than 200 research publications in reputed journals/conference proceedings, and delivered more than 200 invited/keynote lectures in India and abroad.


Advances in Learning Control Techniques for Intelligent Robots

Prof. Xin Xu
National University of Defense Technology, China

In this talk, the requirements of developing new learning control theory and methods for intelligent robots are analyzed. Three major classes of robot learning control techniques, which include iterative learning control, imitation learning, and reinforcement learning, are introduced and some recent advances in these areas are described. The applications of learning control techniques in various intelligent robot systems, such as bionic robots, robot manipulators, humanoid robots, and intelligent vehicles, etc. are discussed. The research challenges and future directions are also analyzed.

Prof. Xin Xu received the B.S. degree in electrical engineering from the Department of Automatic Control, National University of Defense Technology (NUDT), Changsha, P. R. China, in 1996 and the Ph.D. degree in control science and engineering from the College of Mechatronics and Automation (CMA), NUDT. He has been a visiting scientist for cooperation research in the Hong Kong Polytechnic University, University of Alberta, and the University of Strathclyde, respectively. Currently, he is a full professor with the College of Intelligence Science and Technology, National University of Defense Technology.

Prof. Xu’s main research fields include machine learning and autonomous control of robots and intelligent unmanned systems. He received the Distinguished Young Scholars’ Funds of National Natural Science Foundation of China in 2018. He was a recipient of the second-class National Natural Science Award of China and 2 first-class Natural Science Awards of Hunan Province. He has published 2 monographs and more than 170 papers. He is an associate editor of IEEE Transactions on SMC: Systems, Information Sciences, International Journal of Robotics and Automation, associate Editor-in-Chief of CAAI transactions on Intelligence Technology, and an Editorial Board Member of the Journal of Control Theory and Applications.