凸環境における多対多到達回避ゲームのための効率的オンライン最適化による協調防衛配置
Coordinated Defense Allocation in Reach-Avoid Scenarios with Efficient Online Optimization
凸環境での多対多到達回避ゲームにおいて、攻撃者の戦略を事前に知らずにできるだけ多く迎撃するため、防衛ロボットの連合形成と配置をオンライン凸計画と階層的反復法で交互に最適化する手法を提案した。
著者: Junwei Liu, Zikai Ouyang, Jiahui Yang, Hua Chen, Haibo Lu, Wei Zhang
分類: cs.RO
原文アブストラクト
In this paper, we present a dual-layer online optimization strategy for defender robots operating in multiplayer reach-avoid games within general convex environments. Our goal is to intercept as many attacker robots as possible without prior knowledge of their strategies. To balance optimality and efficiency, our approach alternates between coordinating defender coalitions against individual attackers and allocating coalitions to attackers based on predicted single-attack coordination outcomes. We develop an online convex programming technique for single-attack defense coordination, which not only allows adaptability to joint states but also identifies the maximal region of initial joint states that guarantees successful attack interception. Our defense allocation algorithm utilizes a hierarchical iterative method to approximate integer linear programs with a monotonicity constraint, reducing computational burden while ensuring enhanced defense performance over time. Extensive simulations conducted in 2D and 3D environments validate the efficacy of our approach in comparison to state-of-the-art approaches, and show its applicability in wheeled mobile robots and quadcopters.
