To plan the trajectories of a large and heterogeneous swarm, sequential or synchronous distributed methods usually become intractable, due to the lack of global connectivity and clock synchronization, Moreover, the existing asynchronously distributed schemes usually require recheck-like mechanisms instead of inherently considering the other' moving tendency. To this end, we propose a novel asynchronous protocol to allocate the agents' derivable space in a distributed way, by which each agent can replan trajectory depending on its own timetable. Properties such as collision avoidance and recursive feasibility are theoretically shown and a lower bound of protocol updating is provided. Comprehensive simulations and comparisons with five state-of-the-art methods validate the effectiveness of our method and illustrate the improvement in both the completion time and the moving distance. Finally, hardware experiments are carried out, where 8 heterogeneous unmanned ground vehicles with onboard computation navigate in cluttered scenarios at a high agility.

翻译：针对大规模异构集群的轨迹规划问题，由于缺乏全局连通性和时钟同步，序贯或同步分布式方法通常难以处理。此外，现有的异步分布式方案通常需要类似"重新检查"的机制，而非内在地考虑其他智能体的运动趋势。为此，我们提出一种新型异步协议，以分布式方式分配各智能体的可导空间，使每个智能体能够根据自身时间表重新规划轨迹。本文从理论上证明了防碰撞与递归可行性等性质，并给出了协议更新的下界。通过综合仿真及与五种先进方法的对比，验证了该方法的有效性，并展示了其在完成时间和移动距离上的改进。最后进行了硬件实验，8辆带有板载计算的异构无人地面车辆在杂乱场景中以高敏捷性成功导航。