煤矿救援机器人路径平滑算法研究

Research on path smoothing algorithm of coal mine rescue robot

  • 摘要: 针对煤矿救援机器人利用A*算法规划出来的路径存在转折次数多和路径不够平滑等问题,提出了一种基于改进A*算法的煤矿救援机器人路径平滑算法。首先利用Douglas-Peucker(D-P)算法对A*算法产生的全段路径进行处理,剔除路径中的冗余节点,提取出若干路径节点作为关键节点,解决了A*算法路径冗余节点多、路径转折次数多的问题;然后利用三次样条函数对基于关键节点的整段路径进行拟合处理,得到一条平滑的路径,有效缩短了路径长度。仿真实验结果表明,该算法通用性很强,虽然规划时间与A*算法相比略有增加,但规划出来的路径转折次数少,路径长度短,且路径质量高于遗传平滑算法。

     

    Abstract: In view of problems that path planning of the coal mine rescue robot planned by A* algorithm has many path turning points and the path is not smooth enough, a path smoothing algorithm of coal mine rescue robot based on improved A* algorithm was proposed. Firstly, the Douglas-Peucker (D-P) algorithm is used to process the whole path generated by A* algorithm, and eliminate redundant nodes in the path, and extracts several path nodes as key nodes, which solves the problem that there are many redundant nodes and a large number of path turning points of the A* algorithm. Then, the whole path based on the key nodes is fitted by cubic path function, and a smooth path is obtained, which can effectively shorten the path length. The simulation results show that the algorithm has strong universality, although the planning time is slightly increased compared with the A* algorithm, but the planned path turns are few, the path length is short, and the path quality is relatively better than that of the genetic smoothing algorithm.

     

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