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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2005, Vol. 6 Issue ( 6): 12-    DOI: 10.1631/jzus.2005.A0549
    
Neural network and genetic algorithm based global path planning in a static environment
DU Xin, CHEN Hua-hua, GU Wei-kang
Department of Information Science and Electronics Engineering, Zhejiang University, Hangzhou 310027, China; School of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
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Abstract  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.

Key words： Information Science and Electronics Engineering Communication Engineering Mobile robot      Neural network      Genetic algorithm      Global path planning      Fitness function     
Received: 09 May 2004     
CLC:  TP242.6  
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DU Xin
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DU Xin, CHEN Hua-hua, GU Wei-kang. Neural network and genetic algorithm based global path planning in a static environment. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2005, 6( 6): 12-.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2005.A0549     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2005/V6/I 6/12

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