Communication delays can be catastrophic for multiagent systems. However, most existing state-of-the-art multiagent trajectory planners assume perfect communication and therefore lack a strategy to rectify this issue in real-world environments. To address this challenge, we propose Robust MADER (RMADER), a decentralized, asynchronous multiagent trajectory planner robust to communication delay. RMADER ensures safety by introducing (1) a Delay Check step, where an agent keeps receiving trajectories from other agents and storing them, and repeatedly checking if its newly optimized trajectory conflicts with other agents' trajectories, and (2) a two-step trajectory publication scheme. We perform an in-depth analysis of trajectory deconfliction, benchmark studies, and hardware experiments with different network topologies and dynamic obstacles. We show that RMADER outperforms existing approaches by achieving a 100% success rate of collision-free trajectory generation, whereas the next best async. decentr. method only achieves 83% success.

翻译：通信延迟对多智能体系统可能是灾难性的。然而，大多数现有最先进的多智能体轨迹规划器假设完美通信，因此缺乏在真实环境中解决这一问题的策略。为应对这一挑战，我们提出了鲁棒MADER（RMADER），一种对通信延迟鲁棒的去中心化、异步多智能体轨迹规划器。RMADER通过引入（1）延迟检查步骤（智能体持续接收并存储来自其他智能体的轨迹，反复检查其新优化轨迹是否与其他智能体轨迹冲突）和（2）两步轨迹发布方案来确保安全性。我们对轨迹去冲突化进行了深入分析，开展了基准测试研究以及不同网络拓扑和动态障碍物下的硬件实验。结果表明，RMADER在无碰撞轨迹生成方面实现了100%的成功率，优于现有方法，而次优的异步去中心化方法仅有83%的成功率。