Genetic Goal Oriented Path Planning Algorithm for Acute Obstacle Avoidance in Mobile Robot Navigation

被引：0
|
作者：
Yun, Soh Chin [1 ]
Parasuraman, S. [1 ]
Ganapathy, V. [2 ]
机构：
[1] Monash Univ, Sch Engn, Sunway Campus, Jalan Lagoon Selatan 46150, Bandar Sunway, Malaysia
[2] Univ Malaya, Fac Engn, Dept Elect Engn, Kuala Lumpur 50603, Malaysia
来源：
INTELLIGENT ROBOTICS AND APPLICATIONS, PT II | 2010年 / 6425卷
关键词：
Genetic Algorithm (GA); Genetic Controller; Goal Oriented Path Planning Algorithm (GOPPA); Team AmigoBotTM robot and MATLAB;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Current researches in mobile robots aim to build an autonomous and intelligent system which can plan its motion in a static, dynamic and uncertain environment. In this research, Genetic Algorithm (GA) is used to assist the autonomous mobile robot to move, identify the obstacles by learning the environment and reach the desired goal. This study is focused on the development of algorithm for the acute obstacle avoidance behavior. The proposed navigation technique is capable of re-planning the new optimum collision free path in the event of mobile robot encountering any dynamic obstacles. The method is verified using MATLAB simulation and validated the algorithm using Team AmigoBotTM robot. The results obtained from simulation and experiments are discussed at the end of the paper.
引用
收藏
页码：624 / 635
页数：12
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