关键词: 多机器人, 路径跟随, 编队避障, 强化学习

Abstract: Aiming at the obstacle avoidance and trajectory smoothness problem of multi-robot path following and formation in crowd environment, a multi-robot path following and formation algorithm based on deep reinforcement learning was proposed. Firstly, a pedestrian danger priority mechanism was established, which combined with reinforcement learning to design a danger awareness network to enhance the safety of multi-robot formation. Subsequently, a virtual robot was introduced as the reference target for the multirobot, thus transforming path following into tracking control of the virtual robot by the multi-robot, with the purpose of enhancing the smoothness of the robot trajectories. Finally, quantitative and qualitative analysis was conducted through simulation experiments to compare the proposed algorithm with existing ones. The experimental results show that compared with the existing point-to-point path following algorithms, the proposed algorithm has excellent obstacle avoidance performance in crowded environments, which ensures the smoothness of multi-robot motion trajectories.

Key words: multi-robot, path-following, formation obstacle-avoiding, reinforcement lenrning