Making robots trustworthy: Understanding risk and uncertainty for safe autonomy
Date: February 21, 2025 @ 3:00-4:00PM | Location: Gates B03 | Speaker: Anushri Dixit | Affiliation: UCLA
Abstract:
As we deploy robots in increasingly dynamic and unstructured environments with data-driven policies, the need to be able to make guarantees on the reliability and safety of these systems keeps growing. In this talk, I will present two perspectives on uncertainty quantification. First, I will present a conformal prediction-based framework for making in-distribution guarantees on the safety of a learned perception and planning system. Next, I will present a planning framework for out-of-distribution guarantees using coherent risk measures. I will provide the experimental validation of these methods on ground robots for navigation and showcase applications for subterranean search and rescue. Finally, I will present future directions and challenges in attaining reliable autonomy under distribution shifts.
Bio:
Anushri Dixit is an Assistant Professor at the University of California, Los Angeles in Mechanical and Aerospace Engineering. Prior to this, she was a Postdoctoral Researcher at Princeton University in the Intelligent Robot Motion group. She earned her Ph.D. in Control and Dynamical Systems from California Institute of Technology in 2023 and her B.S. in Electrical Engineering from Georgia Institute of Technology in 2017. Her research focuses on motion planning and control of robots in unstructured environments while accounting for uncertainty in a principled manner. Her work on risk-aware methodologies for planning has been deployed on various robotic platforms as a part of Team CoSTAR’s effort in the DARPA Subterranean Challenge. She has received the Outstanding Student Paper Award at the Conference on Decision and Control, Best Student Paper Award at the Conference of Robot Learning, and was selected as a Rising Star in Data Science by The University of Chicago.