《计算机应用研究》|Application Research of Computers

基于改进BIT<sup>*</sup>算法的机器人路径规划研究

Research on robot path planning based on improved BIT<sup>*</sup>

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作者 张伯泉,刘嘉栋
机构 广东工业大学 计算机学院,广州 510006
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文章编号 1001-3695(2022)01-010-0059-05
DOI 10.19734/j.issn.1001-3695.2021.06.0214
摘要 针对BIT<sup>*</sup>存在小样本下路径规划成功率低、冗余大样本下路径规划效率有待提高的问题,提出基于样本增量生成和概率随机几何图的BIT<sup>*</sup>-SP算法,设计了生成样本和选择样本的启发式函数。实验结果表明,BIT<sup>*</sup>-SP算法在小样本下路径规划成功率大幅度提高,且能更快找到初始解;在大样本下能用更短的时间找到一条优秀的路径,规划速度显著提升。该算法鲁棒性高,在简单及复杂环境中都能适用,性能高效。
关键词 路径规划; 移动机器人; BIT<;sup>;*<;/sup>;; 采样算法; 随机几何图
基金项目 国家自然科学基金资助项目(62076074)
本文URL http://www.arocmag.com/article/01-2022-01-010.html
英文标题 Research on robot path planning based on improved BIT<sup>*</sup>
作者英文名 Zhang Boquan, Liu Jiadong
机构英文名 College of Computer,Guangdong University of Technology,Guangzhou 510006,China
英文摘要 Aiming at the problems that BIT<sup>*</sup> has low success rate of path planning under small samples and the efficiency of path planning under redundant large samples is not high enough, this paper proposed BIT<sup>*</sup>-SP algorithm. Also, this paper designed the heuristic functions of generating samples and selecting samples. The experimental results show that BIT<sup>*</sup>-SP algorithm greatly improves the success rate of path planning under small samples, and can find the initial solution faster. In the case of large samples, it can find an excellent path in a shorter time, and the planning speed is significantly improved. The algorithm that can be applied in both simple and complex environments has high robustness and high performance.
英文关键词 path planning; mobile robot; BIT< sup> *< /sup> ; sampling-based; random geometric graph
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收稿日期 2021/6/9
修回日期 2021/8/3
页码 59-63
中图分类号 TP242.6
文献标志码 A