Improved path planning algorithm for mobile robots

被引：2
|
作者：
Sun, Liping [1 ,2 ]
Duan, Xiaoyu [1 ,2 ]
Zhang, Kai [1 ,2 ]
Xu, Pingan [3 ]
Zheng, Xiaoyao [1 ,2 ]
Yu, Qingying [1 ,2 ]
Luo, Yonglong [1 ,2 ]
机构：
[1] Anhui Normal Univ, Sch Comp & Informat, Wuhu 241003, Anhui, Peoples R China
[2] Anhui Normal Univ, Anhui Prov Key Lab Network & Informat Secur, Wuhu 241002, Anhui, Peoples R China
[3] Soochow Univ, Sch Comp Sci & Technol, Suzhou 215006, Peoples R China
来源：
SOFT COMPUTING | 2023年 / 27卷 / 20期
基金：
中国国家自然科学基金;
关键词：
Path planning; Rapidly exploring random tree; Adjacent-relation extension; Repetitive sequence optimization; RRT-ASTERISK; NAVIGATION; OPTIMIZATION; PSO;
D O I：
10.1007/s00500-023-08674-z
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Path planning is an NP-hard problem in road network environments. Considering that the existing path planning algorithms mainly have the problems of low smoothness and low search efficiency in generating paths in large-scale complex environments, an improved rapidly exploring random tree (RRT) algorithm is proposed in this paper. First, the grid method is applied to model the road network environment, and the RRT algorithm based on adjacency expansion is proposed to search the initial path. Then, the strategies of identifying paths and eliminating redundant paths are adopted, respectively, to further optimize the selected paths. Experimental results show that, compared with other path planning algorithms, our algorithm can achieve faster convergence speed, shorter search path, and better smoothness in a complex map of the environment.
引用
收藏
页码：15057 / 15073
页数：17
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