基于深广结合算法的迷宫机器人路径规划技术研究

Research on route planning technology for labyrinth robot based on deep⁃wide combination algorithm

针对矿井中复杂环境下巡检机器人存在路径规划能力较差、任务执行效率偏低的问题,文中将深度和广度路径搜索方法相结合,提出了一种机器人路径规划算法。通过深广融合得到A*路径规划算法,并将其作为全局路径规划的方法。对于算法中存在规划路径过长且平滑度较差的不足,使用人工势能法对局部路径加以优化,以提高路径规划的准确度。同时还利用贝塞尔曲线进行路径平滑操作,进而增强了算法的工程应用能力。实验测试结果表明,该算法在不同尺寸地图中的表现均较为良好,尤其是在大尺寸地图中,其规划的路径最短且运行时间缩短了20 ms以上,证明该算法具有较强的鲁棒性。

Aiming at the shortcomings of poor path planning ability and low task execution efficiency of patrol robot in complex mine environment,this paper proposes a robot path planning algorithm by combining the depth path search algorithm with the breadth path search algorithm.A*path planning algorithm is obtained through the combination of depth and breadth,and is used as the global path planning method.Aiming at the shortcomings of long planned path and poor smoothness in the algorithm,the artificial potential energy method is used to optimize the local path and improve the accuracy of path planning.At the same time,the Bezier curve is used to smooth the path,which enhances the engineering application ability of the algorithm.The experimental results show that the algorithm performs well in different size maps,especially in large size maps.The shortest path planned and the running time shortened by more than 20 ms prove that the algorithm has strong robustness.