ICCAS Frontiers Session
by Joonbum Bae, OS Chair of ICCAS 2021Frontiers in control and robotics fields are introduced, and their recent research is presented.
Date: October 13, Wednesday 09:00-10:30
Place: 8F Room 8 (Halla Hall)
|Prof. Hyun-Min Joe
Department of Robot & Smart System Engineering
Kyungpook National University, Korea
Title: Control Algorithm for Stable Locomotion of a Biped Robot in Uneven Terrain
|Abstract: Research on a terrain-blind walking control that can walk stably on uneven terrain is an important research field for biped robots to achieve human-level walking abilities, and it is still a field that needs much improvement. This presentation describes a robust balance-control algorithm for stable walking of a biped robot in uneven terrain. For robust balance-control against disturbances caused by uneven terrain, we propose a framework that combines a capture-point controller that modifies the control reference, and a balance controller that follows its control references in a cascading structure. The capture-point controller adjusts a zero-moment point reference to stabilize the perturbed capture-point from the disturbance, and the adjusted zero-moment point reference is utilized as a control reference for the balance controller, comprised of foot position, zero-moment point, leg length, and foot orientation controllers. The effectiveness of the proposed control framework was verified by stable walking performance on various uneven terrains, such as slopes, stone fields, and lawns.
|Prof. Jung Hoon Kim
Department of Electrical Engineering
Title: The L1 Problem of Sampled-data Systems
|Abstract: Among a number of system norms, the L infinity-induced norm of a system corresponds to the maximum magnitude of the output for the worst persistent external input with a unit magnitude, and evaluating such a maximum magnitude is quite significant in many control systems since bounded persistent disturbances such as steps and sinusoids are often occurred in real systems.
On the other hand, it could be confirmed for the single-output case that the L infinity-induced norm coincides with the L1 norm for the impulse response, and thus the problem on the treatment of the L infinity-induced norm has been called the L1 problem.
In this talk, the L1 problem of sampled-data systems consisting of a continuous-time plant with a discrete-time controller is considered.
For a given discrete-time controller, the L1 analysis problem of sampled-data systems is first discussed. Then, a method for designing an optimal controller minimizing the L infinity-induced norm of sampled-data systems is introduced. Finally, the L1 robust stability analysis problem is dealt with in this talk.Education
2014.04 – 2015.03 Ph.D in Electrical Engineering, Kyoto University
2012.04 – 2014.03 M.E. in Electrical Engineering, Kyoto University
2008.04 – 2012.03 B.E. in Electrical and Electronic Engineering, Kyoto UniversityProfessional Experience
2019.04 – Present Assistant Professor, Department of Electrical Engineering, POSTECH
2017.05 – 2019.03 Senior Research Scientist, Center for Robotics Research, KIST
2015.06 – 2017.04 Postdoctoral Researcher, Center for Robotics Research, KIST
2015.04 – 2015.05 JSPS Postdoctoral Research Fellow, Kyoto University
2014.04 – 2015.03 JSPS Research Fellow for Young Scientist, Kyoto University
|Prof. Min Jun Kim
Title: Towards Safe Aerial Manipulation in Industrial Scenarios
|Abstract: Aerial manipulation is an emerging research field after success stories of multi-rotor studies which have impacted not only research community but also markets. There are several branches of aerial manipulation studies, but I am particularly interested in performing manipulation tasks in a complex industrial site. Risk management, however, is a keyword that hinders us from performing manipulation tasks in such a complex site, because the crash of an aerial system will essentially cause a big trouble. To deal with this difficulty, we have developed a new system called SAM (stands for cable-Suspended Aerial Manipulator) that inherently minimizes the risk. In this talk, I will introduce design features of SAM, and will introduce how we integrated different functionalities such as self-stabilization of SAM, vision-based object localization, and telemanipulation, in order to accomplish an industrial scenario. This scenario, which is designed under an EU project AEROARMS, includes deployment and retrieval of a robotic crawler for pipe inspection. I will conclude the talk by sharing our ideas on the future directions.
Min Jun Kim received the B.S. degree in mechanical engineering from Korea University, in 2010, and received the Ph.D. degree in mechanical engineering from Pohang University of Science \& Technology (POSTECH), in 2016. From June 2016 to July 2020, he was working as a research scientist in the Institute of Robotics and Mechatronics, German Aerospace Center (DLR). He is currently an assistant professor of Electrical Engineering at Korea Advanced Institute of Science and Technology (KAIST). His research interests include flexible joint robots, physical robot interaction, aerial robots, nonlinear robust control.
|Prof. Cheolhyeon Kwon
Department of Mechanical Engineering
Title: High-assurance Cyber Physical System from Control Theoretic Perspective
|Abstract: Recent years have witnessed a significant growth of Cyber-Physical Systems (CPSs) used in a wide range of control applications from large-scale infra structure to microscale robots. However, due to their close integration of computational resources, physical processes, and communication capabilities, CPSs are exposed to extra complexity compared to conventional control systems. In seeking to address the safety-critical CPS problems, a control theoretic approach is explored extending beyond just the computing process of the CPS to include the underlying physical behaviors, within the context of a unified physical and computing process model of the CPS. In this talk, I briefly go through the current state-of-the-art toward the control-oriented CPS research, along with my on-going contributions to this field.
|Prof. Donghwan Lee
School of Electrical Engineering
Title: Control Theory Meets Reinforcement Learning
|Abstract: Reinforcement learning (RL) is a central topic for machine learning research and artificial intelligent. It addresses the problem of how a decision maker can learn an optimal decision making rule to maximize cumulative rewards, while interacting with unknown environment. RL has recently captured significant attentions in the AI and control community for outperforming human in several challenging tasks, such as Atari video games and AlphaGo. Despite the empirical successes, people have limited understanding on convergence of RLs (especially deep RLs). Motivated by the discussions, we present a dynamic control system perspective of RL algorithms, which unifies both the asymptotic and finite-time convergence analysis of RL algorithms, including Q-learning and its variants. Specifically, we view these RL algorithms as switching systems and then use a unified approach for their convergence certifications based on switching system theory. Our proposed analysis can be automated for a class of RL algorithms under various assumptions. We expect that such control-theoretic analysis could further stimulate the synergy between control theory and RL, provides unified practical tools for analysis of a large family of Q-learnings, and open up opportunities to the design of new RL algorithms. By filling the gap between both domains in a synergistic way, this approach can potentially facilitate further progress in each field.
Donghwan Lee received the B.S. degree in Electronic Engineering from Konkuk University, Seoul, South Korea, in 2008, the M.S. degree in Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea, in 2010, the M.S. degree in Mathematics and the Ph.D. degree in Electrical and Computer Engineering from Purdue University, West Lafayette, IN, USA, in 2017. He was a postdoctoral research associate with the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, IL, USA, from 2017 to 2019. He is currently an assistant professor with the School of Electrical Engineering, KAIST, Daejeon, South Korea. His current research interests include stochastic programming, multi-agent systems, and reinforcement learning.
|Prof. Hae-Won Park
Department of Mechanical Engineering
Title: Model Predictive Control of Dynamic Legged Robots
|Abstract: Controlling legged robots is a challenging control task due to model complexities caused by the mathematically challenging dynamic properties of legged robots, such as high degrees of freedom (DoF), nonlinearity, underactuation, and hybrid nature. Recently, model predictive control (MPC) has received a lot of attention as a control framework for legged robots thanks to its successful application in dynamic walking, high-speed running, and jumping over obstacles. In this talk, I will talk about my recent work on model predictive controller design that achieved dynamic walking and running on multiple hardware platforms in our lab. A novel formulation of MPC on rotation manifold SO(3) and Quadratic Programming solver that efficiently solves formulated optimization problem for MPC are summarized.
Prof. Hae-Won Park is the director of Humanoid Robot Research Center and an Assistant Professor of Mechanical Engineering with the Korea Advanced Institute of Science and Technology (KAIST). He received his B.S. and M.S. degrees from Yonsei University, Seoul, Korea, in 2005 and 2007, respectively, and the Ph.D. degree from the University of Michigan, Ann Arbor, MI, USA, in 2012, all in mechanical engineering. Before joining KAIST, he was an Assistant Professor of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign from 2015 to 2019. His research interests lie at the intersection of control, dynamics, and mechanical design of robotic systems, with special emphasis on legged locomotion robots and bio-inspired robots. Dr. Park is the recipient of NSF CAREER Award from National Science Foundation (2018), Research Prize for Outstanding Faculty from KAIST (2020), and the Best Robocup Award from IEEE/RSJ International Conference on Intelligent Robots and Systems (2019).
|Dr. Sutthiphong Srigrarom
Department of Mechanical Engineering
National University of Singapore, Singapore
Title: Sunlight Compensation for Vision Based Drone Detection
|Abstract: Computer vision based object detection can be applied in security and monitoring scenarios, such as detecting and tracking drone intrusions using cameras. However, its effectiveness is dependent on environmental conditions. For example, under bright sunlight and clear sky conditions, the sunlight reflecting off a target could cause it to blend into the sky and prevent detection. In this paper, an algorithm to compensation for the effects of sunlight on object detection was proposed. The algorithm applied a localised contrast increase to the sky through RGB-HSV conversion and image extraction techniques, which avoided the generation of false positives among the treeline. Preliminary tests with prerecorded videos showed that the algorithm improves detection under bright sunlight conditions but the contrast gain had to be manually tuned. Methods to dynamically tune the gain, and field tests to determine the algorithm’s real time effectiveness, are slated for future work.
Dr. Sutthiphong ‘Spot’ Srigrarom, Dr. Spot was previously an associate professor, aerospace systems, Singapore Institute of Technology-University of Glasgow Singapore (SIT-UGS). He is a visiting professor at Institute of Flight System Dynamics, Technical University of Munich. He is also adjunct associate professor at Singapore University of Technology and Design (SUTD) and Osaka University. His research work is mainly on UAV design, Unmanned Aerial Systems and its applications with deep learning and artificial intelligence (AI), advancements in guidance, navigation, and control (GNC) technology relevant to autonomous vehicles and their payload. He taught the capstone Aerospace Systems Design Project or UAV design course at SIT-UGS since 2012. He has more than 40 publications on UAV applicatiion-related topics. He was the chair of International Conference in Intelligent Unmanned Systems (ICIUS) in 2012. He is an associate editor of Journal of Unmanned System Technology (JUST) under Emerald Publishing (EI-indexed) from 2008 until present. He has several UAV works in his lab ranging from flapping wings, tiltrotors, amphibious, etc. He has supervised and co-supervised 6 PhDs, 2 Masters and more than 100 Bachelors degree students, since 2012. He and his students have been participating in several UAV design and competitions, and have won several accolades in Singapore, Thailand, Taiwan and Korea.