Robot Path Planning by Generalized Ant Colony Algorithm

Dai Yuan Zhang; Peng Fu

doi:10.4028/www.scientific.net/AMM.494-495.1229

Paper Titles

A Simulation Research on the Visual Servo Based on Pseudo-Inverse of Image Jacobian Matrix for Robot
p.1212

Based on Single Chip Microcomputer and C# Carving Machine Control System Design
p.1216

Intelligent Control Emotion Mechanism Based on Artificial Life
p.1220

The Design of Oxygen Content Controller in the Closed Environment
p.1225

Robot Path Planning by Generalized Ant Colony Algorithm
p.1229

Heating Furnace Temperature Control Model Based on Three-Dimensional Fuzzy Neural Network
p.1233

Robust Stability of Sampling System with Input Time-Delay
p.1239

Study on Loss Consumption for Closed Loop Air Suspension Height Control System with High & Low Pressure Chambers
p.1242

Study of PID Control Algorithm Based on the Critical Ratio Method
p.1246

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 494-495Robot Path Planning by Generalized Ant Colony...

Robot Path Planning by Generalized Ant Colony Algorithm

Abstract:

For the problem that the searching speed of traditional ant colony algorithm in robot path planning problem is slow, this paper will solve this problem with generalized ant colony algorithm. Generalized ant colony algorithm extends the definition of ant colony algorithm and does more general research for ant colony algorithm. Functional update strategy replaces the parametric algorithm update strategy; it accelerates the convergence speed of ant colony algorithm. Applying the generalized ant colony algorithm to robot path planning problem can improve the searching speed of robots and reduce the cost of convergence time.

You might also be interested in these eBooks

Current Development of Mechanical Engineering and Energy

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 494-495)

Pages:

1229-1232

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.494-495.1229

Citation:

Cite this paper

Online since:

February 2014

Authors:

Dai Yuan Zhang*, Peng Fu

Keywords:

Ant Colony Algorithm (ACO), Generalized Ant Colony Algorithm, Path Planning, Robot

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Liang Yu-ming, Xu Li-hong. Current status and future development of mobile robot path planning technology [J]. Mechatronics, 2009(3): 35-38.

Google Scholar

[2] Daiyuan Zhang. Convergence Analysis for Generalized Ant Colony Optimization Algorithm.

Google Scholar

[3] Daiyuan Zhang. A new improved generalized ant colony optimization algorithm [J]. Computer technology and development, 2012, 22(6): 39-44.

Google Scholar

[4] Li Guo-dong, Xie Hong-bin, Li Chun-guang. Method of mobile robot path planning in dynamic environment based on genetic algorithm[J]. Robot, 2003, 4(25): 327-330.

Google Scholar

[5] Zhang Jun, Hu Xiao-min, Luo Xun-yao. Ant colony optimization [M]. Beijing: Tsinghua university press, (2007).

Google Scholar

[6] Dorigo M, Luca M. The ant colony algorithm applied to the nuclear reload problem [J]. Annals of Nuclear Energy. 2009, 29(12): 1455-1470.

DOI: 10.1016/s0306-4549(01)00118-9

Google Scholar

[7] Deng Yi-qiao. Generalized ant colony algorithm theory and its application in machine learning.

Google Scholar

[8] Liu Yan-ju, Yang Qing-chuang, Gu Yin-yin. Research of Ant Colony Algorithm for Robot Path Planning [J]. Computer science. 2008, 35(5).

Google Scholar