Observer-Based Environment Robust Control Barrier Functions for Safety-Critical Control With Dynamic Obstacles

This paper proposes a safety-critical controller for dynamic and uncertain environments, leveraging a robust environment control barrier function (ECBF) to improve robustness against the uncertainties associated with moving obstacles. The approach reduces conservatism, compared with a worst-case uncertainty approach, by incorporating a state observer for obstacles into the ECBF design. The safety-guaranteed controller is achieved by efficiently solving a quadratic programming problem. The effectiveness of the proposed method is demonstrated via a dynamic obstacle-avoidance problem for an autonomous vehicle, including comparisons with established baseline approaches.