A Rough Set GA-based Hybrid Method for Robot Path Planning

被引：0
|
作者：
Wu, Cheng-Dong [1 ]
Zhang, Ying [1 ]
Li, Meng-Xin [1 ]
Yue, Yong [2 ]
机构：
[1] Shenyang Jianzhu Univ, Shenyang 110168, Liaoning, Peoples R China
[2] Univ Luton, Luton LU1 3JU, Beds, England
来源：
INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING | 2006年 / 3卷 / 01期
关键词：
Rough sets; genetic algorithms; robot; path planning;
D O I：
10.1007/s11633-006-0029-5
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a hybrid method based on rough sets and genetic algorithms, is proposed to improve the speed of robot path planning. Decision rules are obtained using rough set theory. A series of available paths are produced by training obtained minimal decision rules. Path populations are optimised by using genetic algorithms until the best path is obtained. Experiment results show that this hybrid method is capable of improving robot path planning speed.
引用
收藏
页码：29 / 34
页数：6
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