Bridging rigorous methods with machine learning to build safe and intelligent autonomy
Associate Professor of Aeronautics and Astronautics
Attendance Link: https://docs.google.com/forms/d/e/1FAIpQLSdzU9VehavfTCy6zZk7vXcXHEx-FtcWxWNqa091cx10YlUvSQ/closedform
Abstract
Learning-based controllers now achieve impressive performance on hard robotics and autonomy tasks, but two coupled gaps limit their deployment: we cannot guarantee that a learned policy is safe, and we cannot efficiently find the rare scenarios in which it fails. This talk presents our recent development that closes the loop between synthesis and falsification. On the synthesis side, I will describe how neural certificates can be formulated as value functions in reinforcement learning to produce control policies with safety and stability guarantees, turning safety from a soft penalty into a structural property of the policy. On the verification side, I will present an adaptive test-case generation approach that uses Bayesian active learning to discover scenarios that are both likely to reveal failures and useful for coverage. This method can predict failures from limited hardware demonstrations and support system-level ethical testing through scalable, evolving experimental design.
Bio:
Chuchu Fan is an Associate Professor (pre-tenure) in the Department of Aeronautics and Astronautics (AeroAstro) and Laboratory for Information and Decision Systems (LIDS) at MIT. Before that, she was a postdoc researcher at Caltech and got her Ph.D. at the University of Illinois at Urbana-Champaign. She earned her bachelor’s degree from Tsinghua University. Her research group, Realm at MIT, works on using rigorous mathematics, including formal methods, machine learning, and control theory, for the design, analysis, and verification of safe autonomous systems. Chuchu is the recipient of an NSF CAREER Award, an AFOSR Young Investigator Program (YIP) Award, and the 2020 ACM Doctoral Dissertation Award.
Please visit https://stanfordasl.github.io/robotics_seminar/for this quarter’s lineup of speakers. Although we encourage live in-person attendance, recordings of talks will be posted also.