This paper presents a decentralized multi-agent trajectory planning (MATP) algorithm that guarantees to generate a safe, deadlock-free trajectory in an obstacle-rich environment under a limited communication range. The proposed algorithm utilizes a grid-based multi-agent path planning (MAPP) algorithm for deadlock resolution, and we introduce the subgoal optimization method to make the agent converge to the waypoint generated from the MAPP without deadlock. In addition, the proposed algorithm ensures the feasibility of the optimization problem and collision avoidance by adopting a linear safe corridor (LSC). We verify that the proposed algorithm does not cause a deadlock in both random forests and dense mazes regardless of communication range, and it outperforms our previous work in flight time and distance. We validate the proposed algorithm through a hardware demonstration with ten quadrotors.

翻译：本文介绍了一种分散的多试剂轨迹规划算法(MATP),它保证在有限的通信范围内,在障碍程度有限的环境中创造一个安全、无僵局的轨迹。提议的算法利用基于网格的多试剂路径规划算法(MAPP)解决僵局,我们引入了次级目标优化方法,使代理商在不陷入僵局的情况下聚集到MAPP产生的路口。此外,提议的算法通过采用一条线性安全走廊(LSC)确保优化问题和避免碰撞的可行性。我们核实,拟议的算法不会在随机森林和密集的迷宫中造成僵局,不管通信范围如何,而且它比我们以往在飞行时间和距离方面的工作要快。我们通过10个梯田的硬件示范来验证拟议的算法。