Application of improved ant colony algorithm in mobile robot path planning

doi:10.1117/12.2638700

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	Application of improved ant colony algorithm in mobile robot path planning
	Gao, Xiang 2; Jin, Wuyin 2; Zhang, Xia 1; Zhang, Binfei 2
	2022
会议日期	MAR 25-27, 2022
会议地点	ELECTR NETWORK
关键词	Path planning Ant colony algorithm deadlock Heuristic functions
卷号	12259
DOI	10.1117/12.2638700
英文摘要	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.
源文献作者	Fed Univ Rio Grande,AEIC Acad Exchange Informat Ctr
会议录	2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING, AND INTELLIGENT COMPUTING (CAMMIC 2022)
会议录出版者	SPIE-INT SOC OPTICAL ENGINEERING
语种	英语
ISSN号	0277-786X
WOS研究方向	Computer Science ; Mathematics
WOS记录号	WOS:000836381400199
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/159876]
专题	机电工程学院
作者单位	1.Longdong Univ, Coll Elect Engn, Qingyang 745000, Peoples R China 2.Lanzhou Univ Technol, Sch Mech & Elect Engn, Lanzhou 730050, Peoples R China;
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]. 见:. ELECTR NETWORK. MAR 25-27, 2022.