Path Planning of Mobile Robots Based on the Fusion of an Improved A* Algorithm and a Dynamic Window Approach

摘要

Aiming at the needs of global optimal path planning and real-time obstacle avoidance for mobile robots, a path planning method based on the fusion of an improved A* algorithm and dynamic window approach (DWA) is proposed. First, based on the traditional A* algorithm, a heuristic function is designed to reduce the number of search nodes and the turns of the planned path. Then, the node neighborhood search strategy is improved to optimize the selection of nodes and reduce the probability of collision obstacles. In addition, a key points selection strategy is used to remove redundant nodes and unnecessary turning nodes in the path. Finally, the evaluation function of the dynamic window approach is improved, and the local obstacle avoidance ability and the smoothness of the path are improved on the basis of ensuring the global optimality of the planned path. The simulation experiment results show that compared with the traditional A* algorithm, the above algorithm reduces the number of turns and the turning angle by 57% and 80%, respectively, and can stay away from obstacles in real time. Moreover, the planned path is smoother and safer. Compared with the dynamic window approach, the above algorithm can obtain the globally optimal path, and the local obstacle avoidance ability is more robust.