蚁群融合动态窗口法的分布式多机器人运动规划研究

Research on distributed multi-robot motion planning basedon ant colony algorithm fusion dynamic window approach

为更好地协调分布式多移动机器人在动态环境下的运动,将蚁群算法与动态窗口法相融合构造多机器人系统,并利用优先级策略来化解运动冲突。为提升多机器人全局路径的综合最优性能,提出了多指标寻优的启发式函数和信息素更新策略来提升蚁群的寻优能力,通过冗余点删除策略进一步提升路径质量;融合蚁群与动态窗口法构造机器人运动学模型,通过自适应导航策略来提升未知环境下机器人的局部运动能力;将单机器人避障策略和多移动机器人优先级策略相结合,将多机器人路径规划简化为单个移动机器人的动态路径规划问题。仿真实验结果表明,所提方法能够实现多移动机器人系统在未知环境中的协同避障,具有较高的安全性。

To better coordinate the motion of distributed multi-mobile robots in dynamic environments,this paper constructs a multi-robot system based on a mixture of ant colony algorithm and dynamic window approach and uses a priority strategy to resolve motion conflicts.First,to improve the optimal global performance of multi-robot paths,we propose a multi-indicator optimization-seeking heuristic function and a pheromone update strategy to enhance the optimization capability of the ant colony and further improve the path quality through a redundant point deletion strategy.Secondly,the robot kinematic model is constructed based on a mixture of the ant colony and dynamic window approach,and an adaptive navigation strategy is proposed to improve the local motion of the robot in an unknown environment.Finally,the single-robot obstacle avoidance strategy and the multi-mobile robot prioritization strategy are combined to reduce the multi-robot path planning to a dynamic path planning problem for a single mobile robot.Experimental simulation results show that the proposed method can realize the cooperative obstacle avoidance of the multi-mobile robot system in an unknown environment with high safety.