Global path planning for ALV based on improved glowworm swarm optimization under uncertain environment

被引：0
|
作者：
机构：
[1] College of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing
来源：
Du, P.-Z. (h.k@foxmail.com) | 1600年 / Chinese Institute of Electronics卷 / 42期
关键词：
Autonomous land vehicle (ALV); Glowworm swarm optimization (GSO); Path planning; Path switching; Secondary planning;
D O I：
10.3969/j.issn.0372-2112.2014.03.031
中图分类号：
学科分类号：
摘要：
According to the characteristics of autonomous land vehicle, a global path planning method based on improved glowworm swarm optimization (GSO) is proposed. Firstly, more than one path is generated with GSO which covers multiple local optima. Then two path switching algorithms are proposed, of which one aims at optimization and the other aims at rescue. When the cross point is passed through, the optimization switching algorithm revaluates the paths, switches to the optimum path, and ultimately attains optimal actual travel route. When the environment changes, the rescue switching algorithm switches to the appropriate path by heuristic search, which reuses the original search results, avoiding the secondary planning. Many simulation experiments and actual trial show that the proposed method is feasible and effective.
引用
收藏
页码：616 / 624
页数：8
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