多障碍环境下巡检机器人路径规划优化研究  

Research on path planning optimization of inspection robot in multi-obstacle environment

作　　者：乔道迹[1] 张艳兵 QIAO Daoji;ZHANG Yanbing(School of Computer Science and Technology,North University of China,Taiyuan 030051,China;School of Electrical and Control Engineering,North University of China,Taiyuan 030051,China)

机构地区：[1]中北大学计算机科学与技术学院,山西太原030051 [2]中北大学电气与控制工程学院,山西太原030051

出　　处：《现代电子技术》2025年第1期130-134,共5页Modern Electronics Technique

摘　　要：针对大规模、密集的障碍物分布,高效地搜索最佳路径是一个挑战,为规划出更短的巡检路线,并实现多障碍环境下的灵活避障,文中提出一种多障碍环境下巡检机器人路径规划优化方法。使用二维矩阵构建巡检环境模型,应用D*算法在巡检环境模型中进行巡检机器人路径规划,并将传统D*算法中的扩展步长方式改变为自适应扩展步长,使机器人在面积较大的巡检场地能够更快地完成巡检;将代价函数由欧氏距离替换为切比雪夫诺距离和曼哈顿距离融合的代价函数,并引入了平滑度函数优化线路规划结果,使规划的路径更为平滑,在遇到由于多种原因产生的新障碍物时可以重新规划路径。通过实验结果可知,无论是静态地图还是动态地图,该方法均可以快速准确地规划出一条最佳路线,并且在多种环境中应用该方法能够高效获取路径规划结果。In the case of the large-scale and dense obstacle distributions,it is a challenge to search the best path efficiently.In order to get shorter inspection routes and achieve flexible obstacle avoidance in multi-obstacle environments,a research on path planning optimization methods for inspection robots in multi-obstacle environments is carried out.An inspection environment model is constructed by a two-dimensional matrix.The D*algorithm is applied to plan the path of the inspection robot in the inspection environment model.The means of the extended step size in the traditional D*algorithm is changed to adaptive extended step size,so that the robot can complete inspections faster in larger inspection sites.The cost function is replaced by the one based on the fusion of Chebyshev distance and Manhattan distance.The smoothness function is introduced to optimize the route planning results,which makes the planned path smoother and can be re-planned when encountering new obstacles due to various reasons.It can be concluded with experimental results that the proposed method can plan the optimal route for both static and dynamic maps quickly and accurately,and its application in various environments can obtain path planning results efficiently.

关 键 词：多障碍 巡检机器人 路径规划 D*算法 动态环境 扩展节点 代价函数 扩展步长 

分 类 号：TN911-34[电子电信—通信与信息系统] TP391[电子电信—信息与通信工程]