Path Planning for Mobile Robots Based on Improved Ant Colony Optimization

被引：13

作者：

Hsu, Chen-Chien ^{[1
]}

Hou, Ru-Yu ^{[1
]}

Wang, Wei-Yen ^{[1
]}

机构：

[1] Natl Taiwan Normal Univ, Dept Appl Elect Technol, Taipei, Taiwan

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013) | 2013年

关键词：

colony optimization; path planning; mobile robot; navigation;

D O I：

10.1109/SMC.2013.474

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Although traditional ant colony system (ACS) has the ability of fast convergence, it tends to find local optima. To solve this problem, this paper proposes an improved ant colony system algorithm for path planning of mobile robots by considering two main aspects, including continuous tuning of a setting parameter and the establishment of new mechanisms for pheromone updating. As a result, the ability of global searching of the improved ACS can be significantly enhanced in comparison to the traditional ACS algorithms in deriving an optimal path for mobile robots. Simulation results show the proposed approach has a better performance in terms of shortest distance, mean distance, and successful rate of the optimal paths than those obtained by the traditional ACS algorithms.

引用

页码：2777 / 2782

页数：6

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