- MERL Seminar Series.)
(Learn more about the
Date & Time:
Tuesday, October 10, 2023; 1:00 PM
Inverse Optimal Control (IOC) aims to achieve an objective function corresponding to a certain task from an expert robot driven by optimal control, which has become a powerful tool in many applications in robotics. We will present our recent solutions to IOC based on incomplete observations of systems' trajectories, which enables an autonomous system to “sense-and-adapt", i.e., incrementally improving the learning of objective functions as new data arrives. This also leads to a distributed algorithm to solve IOC in multi-agent systems, in which each agent can only access part of the overall trajectory of an optimal control system and cannot solve IOC by itself. This is perhaps the first distributed method to IOC. Applications of IOC into human prediction will also be given.
Dr. Shaoshuai Mou is the Elmer Bruhn associate professor in the School of Aeronautics and Astronautics at Purdue University. He received a Ph.D. in Electrical Engineering at Yale University in 2014, worked as a postdoc researcher at MIT for a year, and then joined Purdue University as a tenure-track assistant professor in Aug. 2015. His research group Autonomous & Intelligent Multi-agent Systems (AIMS) lab has been focusing on advancing control theories with recent progress in optimization, networks and learning to address fundamental challenges in autonomous systems, with particular research interests in multi-agent systems, control of autonomous systems, learning and adaptive systems, cybersecurity and resilience. Dr. Mou co-directs Purdue’s Institute for Control, Optimization and Networks (ICON) launched in 2020 consisting of more than 85 faculty from 12 departments across Purdue University.