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.Comment: 11 pages, extended version of conference versio