Risk-Aware Decentralized Safe Control via Dynamic Responsibility Allocation (Student Abstract)

Abstract

In this work, we present a novel risk-aware decentralized Control Barrier Function (CBF)-based controller for multi-agent systems. The proposed decentralized controller is composed based on pairwise agent responsibility shares (a percentage), calculated from the risk evaluation of each individual agent faces in a multi-agent interaction environment. With our proposed CBF-inspired risk evaluation framework, the responsibility portions between pairwise agents are dynamically updated based on the relative risk they face. Our method allows agents with lower risk to enjoy a higher level of freedom in terms of a wider action space, and the agents exposed to higher risk are constrained more tightly on action spaces, and are therefore forced to proceed with caution.