School of Mechanical Electronic and Information Engineering, China University of Mining and Technology-Beijing
Key Laboratory of Intelligent Mining and Robotics, Ministry of Emergency Management

路径规划是煤矿机器人在煤矿井下非结构化狭长受限空间中应用亟待解决的关键技术之一。针对传统概率路线图（PRM）算法在空间狭长封闭巷道环境中难以保障采样的节点均匀分布于自由空间中导致路径规划失效，以及节点可能距离障碍物较近导致规划的路径可通行性差等问题，提出了一种基于改进PRM算法的煤矿机器人路径规划方法。在构造阶段引入人工势场法，将落在障碍物中的节点沿与其距离最近自由空间中的节点连线方向推至自由空间，并在障碍物边缘建立斥力场，实现节点的均匀分布且使其距离障碍物有一定距离；在查询阶段融合D* Lite算法，当遇到动态障碍物或前方无法通行时可实现路径的重规划。仿真结果表明：改进PRM算法的节点均匀分布在自由空间中，且均距离障碍物一定距离，提高了路径规划的安全性；当节点数为100个时，改进PRM算法成功率较传统PRM算法提高了25%；随着节点数增加，传统PRM算法和改进PRM算法路径规划成功次数均呈增长趋势，但改进PRM算法在效率方面优势更明显；当节点数为400个时，改进PRM算法运行效率较传统PRM算法提高了35.13%，且规划的路径更平滑，路径长度更短；当障碍物突然出现时，改进PRM算法能够实现路径的重规划。

Path planning is a key technology that urgently need to be solved in application of coal mine robots in unstructured narrow confined spaces underground. The traditional probabilistic road map (PRM) algorithms are difficult to ensure uniform distribution of sampled nodes in free space in narrow and enclosed roadway environments, resulting in path planning failure. Nodes may be close to obstacles, resulting in poor passability of the planned path. In order to solve the above problems, a path-planning method for coal mine robot based on improved PRM algorithm is proposed. In the constructive phase, the artificial potential field method is introduced to push the node falling in the obstacle to the free space along the direction of the connection line of the node in the free space nearest to it. The repulsive force field is established at the edge of the obstacle to realize uniform distribution of nodes and make them a certain distance from the obstacle. In the query phase, the D* Lite algorithm is integrated to achieve path re-planning when encountering dynamic obstacles or when the front is impassable. The simulation results show that the nodes of the improved PRM algorithm are uniformly distributed in free space and are at a certain distance from obstacles. It improves the safety of path planning. When the number of nodes is 100, the success rate of the improved PRM algorithm is 25% higher than that of the traditional PRM algorithm. As the number of nodes increases, the number of successful path-planning attempts for both traditional and improved PRM algorithms shows an increasing trend. But the improved PRM algorithm has a more significant advantage in efficiency. When the number of nodes is 400, the operational efficiency of the improved PRM algorithm is 35.13% higher than that of the traditional PRM algorithms. The planned path is smoother and the path length is shorter. When obstacles suddenly appear, the improved PRM algorithm can achieve path re-planning.

国家自然科学基金面上项目（51874308）；国家重点基础研究发展计划（973计划）项目（2014CB046306）。

0 引言
1 PRM算法原理
2 改进PRM算法
2.1 基于人工势场法的概率地图构建
2.2 基于D*Lite算法的路径搜索
3 实验验证
3.1 融合人工势场法的节点分布评价
3.2 融合人工势场法的概率地图构建评价
3.3 基于D*Lite算法的路径搜索评价
4 结论

薛光辉，刘爽，王梓杰，等. 基于改进概率路线图算法的煤矿机器人路径规划方法[J]. 工矿自动化，2023，49(6)：175-181.

XUE Guanghui, LIU Shuang, WANG Zijie, et al. A path-planning method for coal mine robot based on improved probability road map algorithm[J]. Journal of Mine Automation，2023，49(6)：175-181.