A Novel Multi-robot Path Planning Algorithm Considering Dynamic Environmental Information

Multi-robot path planning is a vital part of Simultaneous localization and mapping (SLAM) systems. In recent years, numerous studies have been conducted in the field of multi-robot path planning. This paper presents a novel method for multi-robot path planning that addresses the challenge of dynamic environments. This method joints adaptive parameters and adaptive steps strategy to the A* algorithm, which greatly improves the operational performance. This paper presents a novel multi-robot path planning method that addresses the challenge of path planning for multiple robots in dynamic environments. In addition, a multi-objective optimization algorithm is introduced and applied to the multi-robot system. To address the issue of dynamic and unknown obstacle avoidance, the rolling window method and obstacle avoidance strategy are utilized. The simulation experiment demonstrates that the proposed algorithm outperforms the CPP-OCA and MAPP-RL algorithms in all three metrics. Additionally, the algorithm’s practical feasibility is verified by applying it to the ROS simulation environment.