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Proceedings Paper

Local path planning of a mobile robot using genetic algorithm
Author(s): Rubo Zhang; Guoyin Zhang; Guochang Gu
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Paper Abstract

The local path planning of mobile robots can be regarded as finding a mapping from perception space to action space. Genetic algorithm is used to search optimal mapping in this paper so as to improve the obstacle avoidance ability of the robot. In this paper, the rotational angle and translation distance of the robot is divided into seven and four grades respectively. In addition, the length of the path that the robot covers before collision with obstacle is taken as fitness. The robot can learn to carry out local path planning through selection, crossover and mutation in genetic algorithm. The simulation results are given at the and of this paper.

Paper Details

Date Published: 12 August 1998
PDF: 6 pages
Proc. SPIE 3366, Robotic and Semi-Robotic Ground Vehicle Technology, (12 August 1998); doi: 10.1117/12.317545
Show Author Affiliations
Rubo Zhang, Harbin Engineering Univ. (China)
Guoyin Zhang, Harbin Engineering Univ. (China)
Guochang Gu, Harbin Engineering Univ. (China)


Published in SPIE Proceedings Vol. 3366:
Robotic and Semi-Robotic Ground Vehicle Technology
Grant R. Gerhart; Ben A. Abbott, Editor(s)

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