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RI Seminar


Soon-Jo Chung Bren Professor of Aerospace and Control and Dynamical Systems Department of Aerospace , Caltech
Friday, September 23
3:30 pm to 4:30 pm
1305 Newell Simon Hall
Safe and Stable Learning for Agile Robots without Reinforcement Learning

Abstract: My research group (https://aerospacerobotics.caltech.edu/) is working to systematically leverage AI and Machine Learning techniques towards achieving safe and stable autonomy of safety-critical robotic systems, such as robot swarms and autonomous flying cars. Another example is LEONARDO, the world’s first bipedal robot that can walk, fly, slackline, and skateboard. Stability and safety are often research problems of control theory, while conventional black-box AI approaches lack much-needed robustness, scalability, and interpretability, which are indispensable to designing control and autonomy engines for safety-critical aerospace and robotic systems. I will present some recent results using contraction-based incremental stability tools for deriving formal robustness and stability guarantees of various learning-based and data-driven control problems, with some illustrative examples including learning-to-fly control with adaptive meta learning, learning-based swarm control and planning synthesis, and optimal motion planning with stochastic nonlinear dynamics and chance constraints. Recent results on neural-network-based contraction metrics (NCMs) as a stability certificate for safe motion planning and control will also be discussed.

Brief Bio: Soon-Jo Chung is Bren Professor of Aerospace and Control and Dynamical Systems in the California Institute of Technology. Prof. Chung is also a Senior Research Scientist of the Jet Propulsion Laboratory, which Caltech manages for NASA. From 2009 to 2016, Prof. Chung was a faculty member at the University of Illinois at Urbana-Champaign. Professor Chung’s research focuses on distributed spacecraft systems, space autonomous systems, and aerospace robotics, and in particular, on the theory and application of control, estimation, learning-based control and planning, and navigation of autonomous space and air vehicles. He is the recipient of the University of Illinois Engineering Dean’s Award for Excellence in Research, the Arnold Beckman Faculty Fellowship of the U of Illinois Center for Advanced Study, the AFOSR Young Investigator Program (YIP) award, the NSF CAREER award, a 2020 Honorable Mention for the IEEE Robotics and Automation Letters Best Paper Award, three best conference paper awards, including the AIAA Guidance, Navigation, and Control Conference and AIAA InfoTech, and five best student paper awards or finalist awards. Prof. Chung is an Associate Editor of the IEEE Transactions on Automatic Control and the AIAA Journal of Guidance, Control, and Dynamics.  He was an Associate Editor of the IEEE Transactions on Robotics, and the Guest Editor of a Special Section on Aerial Swarm Robotics published in the IEEE Transactions on Robotics.

Host: Zac Manchester

For a meeting appointment: Stephanie Matvey (smatvey@andrew.cmu.edu)