A faster path planner using accelerated particle swarm optimization

被引：22
|
作者：
Mohamed, Abdullah [1 ,2 ]
Lee, Sang [2 ]
Hsu, Hung [2 ]
Nath, Namrata [2 ]
机构：
[1] Natl Univ Malaysia UKM, Sch Mat & Mech Engn, Fac Engn & Built Environm, Bangi 43600, Malaysia
[2] Univ South Australia, Sch Adv Mfg & Mech Engn, Div Informat Technol Engn & Environm, Mawson Lakes, SA 5095, Australia
来源：
ARTIFICIAL LIFE AND ROBOTICS | 2012年 / 17卷 / 02期
关键词：
Artificial intelligence; Global path planning; Local path planning; SLAM; Swarm robotics;
D O I：
10.1007/s10015-012-0051-3
中图分类号：
TP24 [机器人技术];
学科分类号：
080202 ; 1405 ;
摘要：
The idea of placing small mobile robots to move around in a large building to detect potential intruders has been around for some time. However, there are still two major hurdles to overcome: to locate itself in the environment and to make a decision on how to move around safely and effectively at a reasonable computation cost. This paper describes a mathematical model for developing a scheme for an autonomous low cost mobile robot system using visual simultaneous localization and mapping and accelerated particle swarm intelligent path planner. The results indicated that this system could provide a solution for the problem of indoor mobile robot navigation. Advances in computer technology make this technique a cost effective solution for a future home service robot.
引用
收藏
页码：233 / 240
页数：8
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