针对未知地图环境下侦察巡检机器人路径规划算法存在的运算耗时较高、响应慢等问题,提出一种适用于未知地图信息情况下的动态路径规划方法及避障策略。首先,改进跳点搜索算法的关键点生成方法,针对大地图动态环境下的搜索需求提出“指定动态跳点”策略;其次,针对“指定动态跳点”策略在凹型障碍物内不易脱离等问题,提出“重搜索”策略;最后,在凹障碍物环境下开展仿真与实验。实验结果表明:在实验环境下,所提路径规划算法能够在保证运行路径较短的同时,规划算法平均耗时降低73.86%,搜索节点数平均减少71.28%,证明所提算法占用设备资源更少,效率更高。
Abstract
To solve the problems of high computational time and slow response in the path planning algorithm of the reconnaissance and inspection robot in the unknown map environment, a dynamic path planning method and obstacle avoidance strategy suitable for unknown map information are proposed.Firstly, improves the key point generation method of the Jump Point Search(JPS) algorithm, and propose a "designated dynamic jump point" strategy for the search requirements in a large map dynamic environment.Secondly, proposes a "re-search" strategy to address the problem of the "designated dynamic jump point" strategy that is not easy to detach from within a concave obstacle.Finally, carries out simulations and experiments in a concave obstacle environment.The experiment results show that in the experimental environment, the proposed path planning algorithm can ensure a shorter running path at the same time.The average time consumption of the planning algorithm is reduced by 73.86%, and the number of search nodes is reduced by 71.28%, which proves that the proposed algorithm occupies less equipment resources and is more efficient.
关键词
侦察巡检机器人 /
动态路径规划 /
跳点搜索
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Key words
reconnaissance and inspection robot /
dynamic path planning /
jump point search
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中图分类号：
TP242
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脚注
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基金
*山东省重大科技创新工程项目(2019JZZY010112);山东省重点研发计划项目(2020JMRH0202);山东大学实验室建设与管理研究重大项目(sy20211301);山东大学教育教学改革研究项目(2020Y211);山东大学教育教学改革研究项目(2021Y264)。
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