基于改进A*算法和动态窗口法的移动机器人路径规划OA

In large scenarios,a hybrid path planning method based on the fusion of the improved A* algorithm and the dynamic window approach(DWA)is proposed in response to the problems of the traditional A* algorithm,such as the large memory overhead,the long search time,and the ease of DWA to fall into the local optimum,and the final path found is not a globally optimal path.Firstly,the 24-neighbourhood expansion of the traditional A* algorithm is reduced to 10-neighbourhood expansion.Secondly,a synchronous bidirectional search strategy is introduced,and based on this,a synchronous direct connection method is proposed to check whether there is an obstacle be-tween two current dynamically defined target nodes,and if there is no obstacle,the final path is generated directly.Then,the critical path points extracted from the global path generated by the improved A* algorithm are used as the local target points of DWA,and the evaluation function of DWA is improved.Finally,the results of simulation and experiment show that compared with the traditional A* algorithm,the improved A* algorithm effectively re-duces the number of traversed nodes by 51.42%and the search time by 63.32%;and the improved DWA can per-fectly avoid concave obstacles and find the globally optimal path.