融合改进A*与DWA算法的机器人路径规划OA

In view of the problems of redundant expansion of nodes in the traditional A* algorithm,the path be-ing close to obstacles,as well as the trajectory oscillation and easy falling into local minima in the traditional DWA(Dynamic Window Approaches)algorithm,this study proposes a robot path planning method that integrates and im-proves the A* and DWA algorithms.The cost function of the traditional A* algorithm is improved to remove redundant expanded nodes.The selection strategy of child nodes is improved to avoid the path being close to obstacles,and un-necessary turning points are removed through bidirectional smoothness optimization.An adaptive distance factor is intro-duced into the evaluation function of the DWA algorithm to reduce the oscillation of the trajectory,and the discrete nodes of the prior path of the A*algorithm are taken as the local target points of the DWA algorithm for algorithm inte-gration.The simulation experiments show that the number of expanded nodes of the improved A* algorithm is reduced by 118,the planning time is reduced by 29.9％,and the planning speed of the improved DWA algorithm is increased by 5.3％.The proposed integrated algorithm can ensure the global optimality of the path,avoid falling into local mini-ma,and achieve real-time obstacle avoidance for unknown obstacles.