Neural network and genetic algorithm based global path planning in a static environment

Mobile robot global path planning in a static environment is an important problem. The paper proposes a method of global path planning based on neural network and genetic algorithm. We constructed the neural network model of environmental information in the workspace for a robot and used this model...

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Bibliographic Details
Published in:Journal of Zhejiang University. A. Science 2005-06, Vol.6 (6), p.549-554
Main Author: 杜歆 陈华华 顾伟康
Format: Article
Language:English
Subjects:
广义路径通道
神经网络
移动机器人
遗传算法
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Summary:Mobile robot global path planning in a static environment is an important problem. The paper proposes a method of global path planning based on neural network and genetic algorithm. We constructed the neural network model of environmental information in the workspace for a robot and used this model to establish the relationship between a collision avoidance path and the output of the model. Then the two-dimensional coding for the path via-points was converted to one-dimensional one and the fitness of both the collision avoidance path and the shortest distance are integrated into a fitness function. The simulation results showed that the proposed method is correct and effective.
ISSN:1673-565X
1009-3095
1862-1775
DOI:10.1631/jzus.2005.A0549