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

页码：233 / 240

页数：8

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