Speaker:    

牟少帅,Purdue University, USA
Inviter:      
Title:
    A Tunable Control/Learning Framework for Autonomous Systems
Language:     Chinese
Time & Venue:
    2023.07.18 10:00-11:00 N533
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.
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