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
DOI10.1117/12.2638700
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
ISSN0277-786X
引用统计
被引频次[WOS]:0   [WOS记录]     [WOS相关记录]
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
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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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