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CLC number: TP242.6

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Received: 2004-05-09

Revision Accepted: 2004-10-07

Crosschecked: 0000-00-00

Cited: 9

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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.6 P.549~554

10.1631/jzus.2005.A0549


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


Author(s):  DU Xin, CHEN Hua-hua, GU Wei-kang

Affiliation(s):  Department of Information Science and Electronics Engineering, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   duxin@zju.edu.cn

Key Words:  Mobile robot, Neural network, Genetic algorithm, Global path planning, Fitness function


DU Xin, CHEN Hua-hua, GU Wei-kang. Neural network and genetic algorithm based global path planning in a static environment[J]. Journal of Zhejiang University Science A, 2005, 6(6): 549~554.

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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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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Open peer comments: Debate/Discuss/Question/Opinion

<1>

amir@bah<amirbahrami50@yahoo.com>

2015-07-20 14:24:19

a good paper

sanaz@deh<s.dehghanipur@gmail.com>

2013-05-16 17:31:57

neural network

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