基于引力场引导的RRT-connect路径规划算法
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北方民族大学 宁夏智能信息与大数据处理重点实验室 银川 750021

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TP301.6

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宁夏自然科学基金项目(2019AAC03121)、宁夏自然科学基金项目(2020AAC03201)、宁夏回族自治区重点研发计划项目(2021BEE03002)、北方民族大学研究生课程建设项目(YKJ202030)、自治区高校本科教育教学改革研究与实践项目(nxbjgZD-5)资助


RRT-connect path planning algorithm based on gravitational field guidance
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North Minzu University, The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia, Yinchuan 750021, China

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    摘要:

    针对双向快速扩展随机树(Rapidly-exploring Random Tree connect,RRT-connect)算法在路径规划过程中耗时长、节点采样随机性大的缺点,提出了基于引力场引导的RRT-connect算法。该算法在路径起点和终点之间设置了第三节点作为新扩展节点,使其在三个节点交替扩展随机树,同时在各节点上分别叠加一个引力场引导节点的产生方向,以降低无效空间的搜索范围。算法在少障碍物、多障碍物以及存在狭窄通道三种场景中进行了仿真实验研究,结果表明改进算法平均迭代次数相比于基础算法降低了47.1%,平均路径规划时间降低了43.4%。证明了改进算法相比于RRT-connect算法能够有效减少规划耗时,具有更高的规划效率。

    Abstract:

    In response to the shortcomings of the Rapidly-exploring Random Tree connect (RRT-connect) algorithm in terms of time consumption and randomness of node sampling during path planning, the RRT-connect algorithm based on gravitational field guidance is proposed. The algorithm sets a third node as a new extension node between the start and end of the path so that it alternates between the three nodes to expand the random tree, while superimposing a gravitational field on each node to guide the direction of node generation in order to reduce the search range of the invalid space. The algorithm was studied in simulation experiments in three scenarios with few obstacles, many obstacles and the presence of narrow passages, and the results showed that the improved algorithm reduced the average number of iterations by 47.1% and the average path planning time by 43.4% compared to the base algorithm. This demonstrates that the improved algorithm can effectively reduce the planning time and has higher planning efficiency than the RRT-connect algorithm.

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赵超力,马行,张春涛,穆春阳.基于引力场引导的RRT-connect路径规划算法[J].电子测量技术,2021,44(22):44-49

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  • 在线发布日期: 2024-07-04
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