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Path Planning of Mobile Robot with A* Algorithm Based on Artificial Potential Field
oleh: CHEN Ji-qing, TAN Cheng-zhi, MO Rong-xian, WANG Zhi-kui, WU Jia-hua, ZHAO Chao-yang
Format: | Article |
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Diterbitkan: | Editorial office of Computer Science 2021-11-01 |
Deskripsi
In order to solve the traditional A* algorithm is not taken into account when planning path obstacle distribution on the influence of the path selection,this paper puts forward an improved A* algorithm,the artificial potential field of thought and the traditional A* algorithm,the combination of the obstacles in grid map gives repulsive force function and the repulsive force around the grid size calculation,in order to improve the searching ability of A* algorithm,the repulsive force of the grid is introduced into the evaluation function of A* algorithm.The results of MATLAB simulation and Turtlebot experiments show that,compared with the traditional A* algorithm,the new improved algorithm combined with artificial potential field algorithm can plan a better path,improve the efficiency of path planning,and increase the search speed by 13.40%~29.68%.The path length is shortened by 10.56%~24.38%,and the number of path nodes is reduced by 6.89%~27.27%.The experimental results show that the improved A* algorithm has obvious optimization effect and is effective and feasible.