Control, Planning, and Learning in Multi-Robot Systems

Abstract

In this presentation, we will explore various robotics projects, spanning underwater robotics, robot manipulation, and multi-robot coordination, conducted in the Robotics, Intelligent Systems, and Control Lab (RISCLab) at King Abdullah University of Science and Technology (KAUST). I will explain the process of designing robots for real-world applications and delve into the research problems our team addresses to overcome some of the technical challenges inherent in deploying robots in these applications. Particularly, the talk will include in-depth discussions on how feedback control methods can be harnessed to develop control, planning, and learning algorithms for these robots and, subsequently, address the technical challenges

Bio

Shinkyu Park is Assistant Professor of Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). Prior to joining KAUST, he was Associate Research Scholar at Princeton University engaged in cross-departmental robotics projects. He received the Ph.D. degree in electrical engineering from the University of Maryland College Park in 2015. Later he held Postdoctoral Fellow positions at the National Geographic Society (2016) and Massachusetts Institute of Technology (2016-2019). Park's research focuses on the learning, planning, and control in multi-agent/multi-robot systems. He is a recipient of 2022 O. Hugo Schuck Best Paper Award (Theory) from the American Automatic Control Council (AACC).