Improved Dynamic Path Planning Algorithm of Mobile Robot Based on Fusion of A* and DWA

Aiming at the problem that mobile robot is prone to collide with random unknown obstacles in the environment during path planning, A dynamic path planning algorithm based on the fusion of A* and DWA was proposed. In the improved A* algorithm, the judgment rules for selecting child nodes are optimized to avoid oblique penetration of obstacle vertices. Secondly, the dynamic ratio K of environmental obstacles is introduced to optimize the heuristic function of the algorithm to improve the search efficiency. Finally, based on Floyd algorithm, redundant nodes in the middle are deleted to increase the smoothness of the path. In the improved DWA algorithm, the gap index in the evaluation function is distinguished according to the known and unknown obstacles, and its weighting coefficients are adjusted respectively to avoid mutual interference and enhance obstacle avoidance ability. The fusion algorithm firstly uses the improved A* algorithm to plan the global optimal path and extract the key nodes of the path. Then, the extracted key nodes are regarded as the subhead of THE DWA algorithm to carry out local path planning in sections. The simulation results show that the improved A* algorithm can reduce the number of turns by 47.8% and the search time by 39.8% on average compared with the traditional A* algorithm. After the fusion of DWA algorithm, the local path can be modified based on the global optimal path, and the dynamic obstacle avoidance to unknown obstacles is realized, which verifies the effectiveness and feasibility of the algorithm.