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     Research Journal of Applied Sciences, Engineering and Technology


Robot Global Path Planning Based on Improved Artificial Fish-Swarm Algorithm

1, 2Jiansheng Peng, 1Xing Li, 3Zhi-Qiang Qin and 2Guan Luo
1China Institute of Atomic Energy, P.O. Box 275-36, Beijing, 102413, China
2Department of Physics and Electronic Engineering, Hechi University, Yizhou, Guangxi, 546300, China
3Hunan University of Science and Technology, Xiangtan, Hunan, 411201, China
Research Journal of Applied Sciences, Engineering and Technology  2013  6:2042-2047
http://dx.doi.org/10.19026/rjaset.5.4747  |  © The Author(s) 2013
Received: July 26, 2012  |  Accepted: September 08, 2012  |  Published: February 21, 2013

Abstract

In This study, a new artificial fish-swarm optimization, to improve the foraging behavior of artificial fish swarm algorithm is closer to reality in order to let the fish foraging behavior, increase a look at the link (search) ambient, after examining environment, artificial fish can get more status information of the surrounding environment. Artificial fish screened from the information obtained optimal state for the best direction of movement. Will improve the foraging behavior of artificial fish-swarm algorithm applied to robot global path planning, including the robot to bypass the analog obstacles selected three ways: go obstructions outside, go inside the obstacles, both away obstructions and went outside obstacles Thing achieve robot shortest path planning. Via the MATLAB software emulation test: the improved foraging behavior of artificial fish-swarm algorithm to improve the rapid convergence of the algorithm and stability, improve fish swarm algorithm to the adaptability of the robot global path planning.

Keywords:

Artificially shoals algorithm, optimal algorithm, robot path planning,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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