Path Planning and Obstacle-Avoidance for Soccer Robot Based on Artificial Potential Field and Genetic Algorithm

Author

Xu, Xinying ; Xie, Jun ; Xie, Keming

Author_Institution

Coll. of Inf. Eng., Taiyuan Univ. of Technol.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3494

Lastpage

3498

Abstract

It is a key problem in the robot soccer game that is the global path planning and obstacle-avoidance of the soccer robots. The path planning is always gotten into the local minimum value solved by the traditional artificial potential field (APF). However, it can be improved by genetic algorithm (GA). In this paper, a novel algorithm (APFGA) combining APF with GA is put forward for the path planning and obstacle-avoidance. First, the algorithm confirms the effective area of obstacle-avoidance and the manner of path generation based on APF, and then it adopts the compact fitness function and designs the genetic operators in detail. Furthermore, the author uses the least square method for curve fitting. In the end, the simulation results indicate that the soccer robot can avoid the obstacles and explore the optimal path by the algorithm presented in this paper

Keywords

curve fitting; genetic algorithms; least mean squares methods; mobile robots; multi-robot systems; path planning; artificial potential field; curve fitting; genetic algorithm; least square method; obstacle-avoidance; path planning; robot soccer game; soccer robots; Algorithm design and analysis; Automation; Curve fitting; Educational institutions; Genetic algorithms; Genetic engineering; Intelligent control; Intelligent robots; Least squares methods; Path planning; artificial potential field; genetic algorithm; path planning; soccer robot;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713018

Filename

1713018