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基于融合A*-蚁群优化算法的移动机器人全局优化

方文凯 廖志高

现代制造工程Issue(7):77-84,8.
现代制造工程Issue(7):77-84,8.DOI:10.16731/j.cnki.1671-3133.2024.07.010

基于融合A*-蚁群优化算法的移动机器人全局优化

Global optimization of mobile robot based on fusion A*-ant colony optimization algorithm

方文凯 1廖志高2

作者信息

  • 1. 广西科技大学经济与管理学院,柳州 545006
  • 2. 广西科技大学经济与管理学院,柳州 545006||广西工业高质量发展研究中心,柳州 545006
  • 折叠

摘要

Abstract

Aiming at the problems of traditional ant colony algorithm in global path planning of indoor mobile robot,such as low search efficiency,unsmooth path,easy to fall into local optimum and deadlock,an ant colony optimization algorithm for bi-direc-tional search with improved A*algorithm was designed.Firstly,the improved A*algorithm was used to quickly converge and ob-tain the initial path in the grid environment,the initial pheromone matrix was constructed,and the obstacle factor was introduced to reduce the occurrence of ant deadlock.Secondly,the rules of ant colony optimization algorithm for bi-directional search were set,the heuristic function model in bi-directional search was improved,and elite ant search strategy and adaptive pheromone volat-ilization factor strategy were introduced.Finally,the third-order Bezier curve was used to smooth the path.The simulation results on Pycharm platform show that this algorithm combines the strong global search ability of A*algorithm and the positive feedback characteristics of ant colony algorithm,which makes the improved algorithm optimize the path length by 12.85%and 7.76%,the search time by 38.17%and 23.46%,and the iteration times by 67.71%and 54.41%compared with the traditional ant colony algorithm and the sparrow search algorithm,and the global path optimization effect is obvious.

关键词

移动机器人/A*算法/蚁群算法/双向搜索路径/贝塞尔曲线

Key words

mobile robot/A*algorithm/ant colony algorithm/bi-directional search path/Bezier curve

分类

信息技术与安全科学

引用本文复制引用

方文凯,廖志高..基于融合A*-蚁群优化算法的移动机器人全局优化[J].现代制造工程,2024,(7):77-84,8.

基金项目

国家自然科学基金面上项目(71771157) (71771157)

广西自动检测技术与仪器重点实验室开放基金项目(YQ20208) (YQ20208)

2020年广西汽车零部件与整车技术重点实验室自主研究课题项目(2020GKLACVTZZ01) (2020GKLACVTZZ01)

现代制造工程

OA北大核心CSTPCD

1671-3133

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