Multi-Agent Reach-Avoid Games: Two Attackers Versus One Defender and Mixed Integer Programming

TL;DR

This paper introduces a hybrid approach combining Hamilton-Jacobi reachability and mixed-integer programming to solve complex multi-agent reach-avoid games, enabling effective defender assignment and capturing strategies in high-dimensional scenarios.

Contribution

It presents a novel hybrid method for multi-agent reach-avoid games, deriving optimal winning sets and optimizing defender assignments using MIP, extending previous approaches to more attackers and defenders.

Findings

Successfully derived optimal winning sets for 2 vs. 1 attacker-defender scenarios.

Demonstrated the effectiveness of the method in numerical simulations.

Extended the approach to scenarios with multiple attackers and fewer defenders.

Abstract

We propose a hybrid approach that combines Hamilton-Jacobi (HJ) reachability and mixed-integer optimization for solving a reach-avoid game with multiple attackers and defenders. The reach-avoid game is an important problem with potential applications in air traffic control and multi-agent motion planning; however, solving this game for many attackers and defenders is intractable due to the adversarial nature of the agents and the high problem dimensionality. In this paper, we first propose an HJ reachability-based method for solving the reach-avoid game in which 2 attackers are playing against 1 defender; we derive the numerically convergent optimal winning sets for the two sides in environments with obstacles. Utilizing this result and previous results for the 1 vs. 1 game, we further propose solving the general multi-agent reach-avoid game by determining the defender assignments that can maximize the number of attackers captured via a Mixed Integer Program (MIP). Our method generalizes previous state-of-the-art results and is especially useful when there are fewer defenders than attackers. We validate our theoretical results in numerical simulations.