Safe Control from Value Functions: Blending Control Barrier Functions and Hamilton-Jacobi Reachability Analysis

Date:  3/16/23

Speaker:  Sylvia Herbert

Location: Zoom

Time: 2:40 p.m.-3:30 p.m.

Abstract:  Value functions have been used extensively for generating safe control policies for robots and other nonlinear systems. The output of the function provides the current “safety level” of the system, and its gradient informs the allowable control inputs to maintain safety.Two common approaches for value functions are control barrier functions (CBFs) and Hamilton-Jacobi (HJ) reachability value functions.  Each method has its own advantages and challenges.  HJ reachability analysis is a constructive and general method that struggles from computational complexity.  CBFs are typically much simpler, but are challenging to find, often resulting in conservative or invalid hand-tuned or data-driven approximations.In this talk I will discuss our work in exploring the connections between these two approaches in order to blend the theory and tools from each.  I’ll introduce the “control barrier-value function,” and show how we can refine CBF approximations to recover the maximum safe set and corresponding control policy for a system.

Bio:   Sylvia Herbert started as an Assistant Professor in Mechanical and Aerospace Engineering at UC San Diego in 2021. She runs the Safe Autonomous Systems Lab within the Contextual Robotics Institute.

Previously she was a PhD student with Prof. Claire Tomlin at UC Berkeley.  She is the recipient of the ONR Young Investigator Award, NSF GRFP, a UC Berkeley Outstanding Graduate Student Instructor Award, and the UC Berkeley Demetri Angelakos Memorial Achievement Award for Altruism.