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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.
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Received: 09 May 2004
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