Path planning of underground mining area transportation scene based on improved A* algorithm
Tianliang Liu, Zhen Huang, Changhai Wang, Ziqi An, Xingzhao Meng, Jianwu Zheng · 2023
The traditional A*algorithm has the problem of being close to obstacles in path planning. For the narrow transportation scene in the underground mining area, it is evident that the algorithm cannot provide a safe path. This paper proposes an improved A*algorithm that introduces the cost of obstacles. The cost of obstacles in the scene is considered in the heuristic function, and a safer feasible path is obtained by smoothing. The experimental site is built for actual vehicle experiments. The results show that the improved A*algorithm with obstacle cost can meet the actual driving needs of intelligent mining vehicles in underground mining transportation scenarios.