Global Path Planning Based on Neural Network and Genetic Algorithm in A Static Environment
نویسندگان
چکیده
Mobile robot global path planning in a static environment is an important problem all along. The paper proposes a method of global path planning based on neural network and genetic algorithm. The neural network model of environmental information in the workspace for a robot is constructed. Using this model, the relationship between a collision avoidance path and the output of the model is established. Then the two-dimensional coding for the via-points of path is converted to one-dimensional one and the fitness of the collision avoidance path and that of the shortest distance are fused to a fitness function. The simulation results show that the proposed method is correct and effective.
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