未知环境中基于A*算法改进的遍历式路径规划算法

针对如何减少未知环境中因复杂地形造成规划路径中存在无效重复路径段问题，提出APF-A*算法。采 用最近邻边界点选择策略保证规划路径对未知环境的高覆盖率，利用人工势场算法改进传统A*算法中估值函数。算 法在栅格地图上进行了实验验证。结果表明：APF-A*算法规划出的路径与A*算法相比在路径总长度方面降低了5.3% 以上，在平均路径重复率方面降低了5.4%以上，APF-A*算法有效减少了无效重复路径段。

A Modified Ergodic Path Planning Algorithm Based on A * Algorithm in Unknown Environment

APF-A* algorithm is proposed to solve the problem of how to reduce the invalid repeated path segments caused by complex terrain in unknown environment. The nearest-neighbor boundary point selection strategy is used to ensure the high coverage rate of the planned path in the unknown environment, and the artificial potential field algorithm is used to improve the evaluation function of the traditional A * algorithm. The algorithm is tested on a grid map. The results show that the path planned by APF-A* algorithm reduces the total path length by more than 5.3% and the average path repetition rate by more than 5.4% compared with the A* algorithm. This proves that the APF-A* algorithm can effectively reduce invalid duplicate path segments.