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

智能仿生算法在移动机器人路径规划优化中的应用综述

Survey on application of bioinspired intelligent algorithms in path planning optimization of mobile robots

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作者 于振中,李强,樊启高
机构 江南大学 物联网工程学院,江苏 无锡 214000
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文章编号 1001-3695(2019)11-002-3210-10
DOI 10.19734/j.issn.1001-3695.2018.07.0483
摘要 随着移动机器人应用领域的扩大和工作环境的复杂化,传统路径规划算法因其自身局限性变得难以满足人们的要求。近年来,智能仿生算法因其群集智慧和生物择优特性而被广泛应用于移动机器人路径规划优化中。首先,按照智能仿生算法仿生机制的来源,对应用于路径规划优化中的智能仿生算法进行了分类。然后,按照不同的类别,系统的叙述了各种新型智能仿生算法在路径规划优化中取得的最新研究成果,总结了路径规划优化过程中存在的问题以及解决方案,并对算法在路径规划优化中的性能进行了比较分析。最后对智能仿生算法在路径规划优化中的研究方向进行了探讨。
关键词 智能仿生算法; 仿生机制; 移动机器人; 路径规划优化; 收敛速度; 局部最优
基金项目 国家自然科学基金资助项目(51405198)
江苏省自然科学基金资助项目(BK20130159)
本文URL http://www.arocmag.com/article/01-2019-11-002.html
英文标题 Survey on application of bioinspired intelligent algorithms in path planning optimization of mobile robots
作者英文名 Yu Zhenzhong, Li Qiang, Fan Qigao
机构英文名 School of Internet of Things Engineering,Jiangnan University,Wuxi Jiangsu 214000,China
英文摘要 With the expansion of the fields of mobile robot applications and the complication of its working environment, traditional path planning algorithms become difficult to meet people's requirements due to their own limitations. In recent years, bioinspired intelligent algorithms(BIAs) are widely used in mobile robot path planning optimization because of its collective intelligence of the group and the characteristics of biological preference. First, this paper classified the bioinspired intelligent algorithms used in the path planning optimization according to their sources of the biomimetic mechanism. Then, to optimize the latest research results and summarize existing problems and solutions, it described systematically various new bioinspired intelligent algorithms used in the path planning optimization according to different categories, and also provided a detailed comparison and analysis of the algorithms performance in path planning optimization. Finally, it discussed further research direction about bioinspired intelligent algorithms.
英文关键词 bioinspired intelligent algorithms; biomimetic mechanism; mobile robot; path planning optimization; convergence speed; local optimal
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收稿日期 2018/7/27
修回日期 2018/9/17
页码 3210-3219
中图分类号 TP18
文献标志码 A