一种基于概率路线图的月球巡航车路径规划算法

为提高月球巡航车自主探测时的安全，提出一种基于概率路线图(Probabilistic Roadmap, PRM)的改进路径规划算法.该算法基于距离变换地图，改善PRM算法的采样方式，控制采样点远离障碍物，使规划的路径远离障碍物，避免紧贴障碍物前进的危险情况，提高了月球巡航车自主探测过程中的安全程度.为评估路径的安全性，提出安全警戒系数和最小安全警戒系数两个安全指标，并在月球表面仿真环境下对A*，PRM和改进的PRM算法生成的路径进行安全评估.结果表明改进的PRM算法相较于A*算法，安全警戒系数和最小安全警戒系数分别提升了2.20 m，1.00 m；相较于PRM算法，安全警戒系数和最小安全警戒系数分别提升了1.68 m，1.00 m.改进的PRM算法不局限于月球巡航车的路径规划，还可以应用于对路径安全性要求较高的探索机器人和自动驾驶汽车.

A Path Planning Algorithm for Lunar Cover Based onProbabilistic Roadmap

To improve the safety of lunar rover during autonomous detection, an improved path planning algorithm based on Probabilistic Roadmap (PRM) is proposed. The algorithm is based on the distance transform map to improve the sampling method of the PRM algorithm. By controlling the sampling point away from obstacles, the planned path is kept away from obstacles, avoiding dangerous situations of advancing close to obstacles, and improving the safety of lunar rover. To evaluate the safety of the path, two safety indicators, a safety alert factor and a minimum safety alert factor, are proposed. And the paths generated by A*, PRM and the improved PRM algorithm are evaluated for safety in the lunar surface simulation environment. The results show that the improved PRM, compared with A* algorithm, the safety alert coefficient and the minimum safety alert coefficient of the algorithm are increased by 2.20m and 1.00m respectively; compared to the PRM algorithm, the safety alert coefficient and the minimum safety alert coefficient are increased by 1.68m and 1.00m, respectively. The improved PRM algorithm is not only limited to the path planning of lunar rover, but can also be applied to exploration robots and self driving cars that require high path safety.