Evolutionary approach to navigation learning in autonomous mobile robot

被引：0

作者：

Wang, Fei ^{[1
]}

Kamano, Takuya ^{[1
]}

Yasuno, Takashi ^{[1
]}

Harada, Hironobu ^{[1
]}

机构：

[1] Northeastern Univ, Inst Artificial Intelligence & Robot, Shenyang 110004, Liaoning Prov, Peoples R China

来源：

PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE: 50 YEARS' ACHIEVEMENTS, FUTURE DIRECTIONS AND SOCIAL IMPACTS | 2006年

关键词：

AMR; navigation; GA; fuzzy rules;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes a method to solve navigation learning problem in autonomous mobile robot (AMR) by evolutionary approach. To achieve both successful navigation to the goal and the suitable obstacle avoidance, the AMR controller parameters are coded as genotype and tuned by genetic algorithm (GA). The danger-degrees which represent the instinctive human knowledge for environment recognition and are calculated by using the fixed fuzzy rules are incorporated into fitness function to evaluate the controller's performance. Experimental results demonstrate the validity of proposed navigation system.

引用

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页码：268 / 270

页数：3

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