Path planning method for mobile robot based on ant colony optimization algorithm

被引：9

作者：

Cen, Yuwan ^{[1
]}

Song, Choingzhi ^{[1
]}

Xie, Nenggang ^{[1
]}

Wang, Lu ^{[1
]}

机构：

[1] Anhui Univ Technol, Sch Mech Engn, Maanshan 243002, Anhui, Peoples R China

来源：

ICIEA 2008: 3RD IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, PROCEEDINGS, VOLS 1-3 | 2008年

关键词：

ant colony optimization (ACO); particle swarm optimization algorithm (PSO); path planning; mobile robot; process industry;

D O I：

10.1109/ICIEA.2008.4582528

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A novel path planning approach based on ACO was presented aiming at mobile robots in structured environments. The information of environment constrains and path length was integrated in the fitness function which was computed by neural network, the path nodes were viewed as an ant, so with the quality of optimization of ant colony optimization algorithm, the best path was found. Finally by computer simulation, it is got that the algorithm is rational and can be used in process industry warehouse patrol measurement mobile robot real-time navigation.

引用

页码：298 / 301

页数：4

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