Decentralized Deadlock-free Trajectory Planning for Quadrotor Swarmin Obstacle-rich Environments

* Status: accepted for publication in IEEE International Conference on Robotics and Automation (ICRA) 2023
* Category: Multi-robot Systems
* Authors: Jungwon Park, Inkyu Jang, and H. Jin Kim
* Abstract: 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.
* Contact: [e-mail]
* Supplementary material: None