AEM Colloquium: A Tunable Control/Learning Framework for Autonomous Systems
Shaoshuai Mou, April 28, 2:30pm
Purdue University, School of Aeronautics and Astronautics
Title: A Tunable Control/Learning Framework for Autonomous Systems
Abstract: Modern society has been relying more and more on engineering advance of autonomous systems, ranging from individual systems (such as a robotic arm for manufacturing, a self-driving car, or an autonomous vehicle for planetary exploration) to cooperative systems (such as a human-robot team, swarms of drones, etc). In this talk we will present our most recent progress in developing a fundamental framework for learning and control in autonomous systems. The framework comes from a differentiation of Pontryagin’s Maximum Principle and is able to provide a unified solution to three classes of learning/control tasks, i.e. adaptive autonomy, inverse optimization, and system identification. We will also present applications of this framework into human-robot teaming, especially in enabling an autonomous system to take guidance from human operators, which is usually sparse and vague. In addition, we will briefly introduce our recent progress in developing control methods for aerospace systems applications.
Bio: 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 100 faculty from more than 15 departments across Purdue University.
