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基于改进A*算法的燃气微泄漏四足巡检机器人路径规划
引用本文:肖瑶,王强,金仲平,唐奇超,巫宇航,贺韬宇.基于改进A*算法的燃气微泄漏四足巡检机器人路径规划[J].科学技术与工程,2024,24(13):5421-5426.
作者姓名:肖瑶  王强  金仲平  唐奇超  巫宇航  贺韬宇
作者单位:中国计量大学 质量与安全工程学院;台州市特种设备检验检测研究院
基金项目:浙江省尖兵领雁研发攻关计划项目(2022C03179);浙江省万人计划科技创新领军人才项目(2019R52017)
摘    要:针对四足机器人在城市燃气微泄漏巡检中路径规划的需求,提出了一种基于改进A*算法的四足机器人燃气巡检路径获取方法。首先,采用网格法构建了四足机器人的二维工作地图。然后改进A*算法的启发函数,引入了自适应调整策略,让搜索节点减少且路径更不易陷入局部最优。最后从路径长度、平均搜索时间、搜索节点个数三个性能方面进行评估,改进A*算法达到了预期效果。使用Matlab2016b作为仿真软件,仿真结果显示,改进A*算法完成了寻路任务。与经典A*算法相比,改进算法的平均搜索时间降低了52.13%,搜索节点个数减少了30.23%。该算法在尺寸200×200以下地图的路径规划中具有较高的搜索效率。

关 键 词:燃气巡检  路径规划  A*算法  四足机器人  环境建模
收稿时间:2023/5/29 0:00:00
修稿时间:2023/9/21 0:00:00

Path planning of gas micro-leakage quadruped inspection robot based on improved A* algorithmy
Xiao Yao,Wang Qiang,Jin Zhongping,Tang Qichao,Wu Yuhang,He Taoyu.Path planning of gas micro-leakage quadruped inspection robot based on improved A* algorithmy[J].Science Technology and Engineering,2024,24(13):5421-5426.
Authors:Xiao Yao  Wang Qiang  Jin Zhongping  Tang Qichao  Wu Yuhang  He Taoyu
Institution:College of Quality and Safety Engineering, China Jiliang University
Abstract:Aiming at the requirement of path planning of the quadruped robot in urban gas micro-leakage inspection, a path acquisition method for gas inspection of quadruped robots based on improved A* algorithm was proposed. Firstly, the grid method was used to construct a two-dimensional working map of the quadruped robot. Then, the heuristic function of A* algorithm was improved, and the adaptive adjustment strategy was introduced to reduce the number of search nodes and make the search path less prone to local optimal. Finally, the improved A* algorithm achieved the expected effect when evaluating from path length, average search time and number of search nodes. Using Matlab2016b as the simulation software, the simulation results show that the improved A* algorithm successfully completes the pathfinding task. Compared with the classical A* algorithm, the average search time of the improved algorithm is reduced by 52.13%, and the number of search nodes is reduced by 30.23%. The algorithm has higher search efficiency in the path planning of maps with size less than 200×200.
Keywords:Gas inspection  path planning  A* algorithm  quadruped robot  Environmental modeling
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