论文标题
在障碍物充足的环境中，四型群的分散僵局轨迹计划 - 扩展版本
Decentralized Deadlock-free Trajectory Planning for Quadrotor Swarm in Obstacle-rich Environments -- Extended version
论文作者
论文摘要
本文介绍了一个分散的多代理轨迹计划（MATP）算法，该算法保证在有限的沟通范围内在障碍物充足的环境中生成安全，无僵硬的轨迹。提出的算法利用基于网格的多代理路径计划（MAPP）算法进行死锁解决方案，我们引入了亚目标优化方法，使代理会收敛到从MAPP产生的无僵局中生成的路点。此外，提出的算法通过采用线性安全走廊（LSC）来确保优化问题和碰撞的可行性。我们验证所提出的算法不会在随机森林和密集的迷宫中造成僵局，而不论沟通范围如何，并且在飞行时间和距离方面都表现出色。我们通过使用十个二次运动的硬件演示来验证提出的算法。
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.
