Distributed Risk-Sensitive Safety Filters for Uncertain Discrete-Time Systems

TL;DR

This paper introduces a distributed risk-sensitive safety filter for uncertain multi-agent discrete-time systems, combining centralized safety conditions with distributed strategies to ensure robustness and feasibility.

Contribution

It presents a novel risk-sensitive safety filter leveraging control barrier functions, with two distributed strategies for robustness and feasibility in uncertain multi-agent systems.

Findings

Effective safety maintenance demonstrated in numerical evaluations

Distributed strategies ensure safety without excessive conservatism

Robustness against model uncertainties confirmed through simulations

Abstract

Ensuring safety in multi-agent systems is a significant challenge, particularly in settings where centralized coordination is impractical. In this work, we propose a novel risk-sensitive safety filter for discrete-time multi-agent systems with uncertain dynamics that leverages control barrier functions (CBFs) defined through value functions. Our approach relies on centralized risk-sensitive safety conditions based on exponential risk operators to ensure robustness against model uncertainties. We introduce a distributed formulation of the safety filter by deriving two alternative strategies: one based on worst-case anticipation and another on proximity to a known safe policy. By allowing agents to switch between strategies, feasibility can be ensured. Through detailed numerical evaluations, we demonstrate the efficacy of our approach in maintaining safety without being overly conservative.