Application of improved ant colony algorithm in mobile robot path planning | |
Gao, Xiang1; Jin, Wuyin1; Zhang, Xia2; Zhang, Binfei1 | |
2022 | |
会议名称 | 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC) |
会议录名称 | 2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING, AND INTELLIGENT COMPUTING (CAMMIC 2022) |
卷号 | 12259 |
会议日期 | MAR 25-27, 2022 |
会议地点 | ELECTR NETWORK |
会议录编者/会议主办者 | Fed Univ Rio Grande,AEIC Acad Exchange Informat Ctr |
出版者 | SPIE-INT SOC OPTICAL ENGINEERING |
摘要 | Aiming at the shortcomings of slow convergence speed and many turning points of the traditional ant colony algorithm in the global path planning of mobile robot, an improved ant colony algorithm is proposed. By adding obstacle information to improve the distance heuristic function, the probability of ants entering the deadlock path is reduced, and the number of effective search is increased. The adaptive adjustment strategy is used to design the dynamic adjustment mechanism of pheromone heuristic factor, which improves the development of the algorithm in the initial stage and takes into account the convergence in the later stage. The second search strategy is introduced to simplify the path points of ant colony algorithm and reduce the redundancy. Experiments show that the improved algorithm has good adaptability in complex environments, and the comprehensive performance index of the final path is better than that of the traditional algorithm, which can provide effective reference for the global path planning of robots in practical environments. |
关键词 | Path planning Ant colony algorithm deadlock Heuristic functions |
DOI | 10.1117/12.2638700 |
收录类别 | CPCI-S ; EI |
语种 | 英语 |
WOS研究方向 | Computer Science ; Mathematics |
WOS类目 | Computer Science, Interdisciplinary Applications ; Mathematics, Applied |
WOS记录号 | WOS:000836381400199 |
EI入藏号 | 20222612274520 |
EI主题词 | Motion planning |
EI分类号 | 723.1 Computer Programming ; 731.5 Robotics ; 921.5 Optimization Techniques |
ISSN | 0277-786X |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/159876 |
专题 | 机电工程学院 |
通讯作者 | Gao, Xiang |
作者单位 | 1.Lanzhou Univ Technol, Sch Mech & Elect Engn, Lanzhou 730050, Peoples R China; 2.Longdong Univ, Coll Elect Engn, Qingyang 745000, Peoples R China |
第一作者单位 | 兰州理工大学 |
通讯作者单位 | 兰州理工大学 |
推荐引用方式 GB/T 7714 | Gao, Xiang,Jin, Wuyin,Zhang, Xia,et al. Application of improved ant colony algorithm in mobile robot path planning[C]//Fed Univ Rio Grande,AEIC Acad Exchange Informat Ctr:SPIE-INT SOC OPTICAL ENGINEERING,2022. |
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