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Kinematics Decoupling of Mobile Robot Based on RBF Neural Network and Genetic Algorithm

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3 Author(s)
Wuxin Huang ; Coll. of Mechatron. Eng. & Autom., Shanghai Univ., Shanghai, China ; ShiLi Tan ; Xiaowei Feng

The mobile manipulator is a multivariable and non-linear system, so the research about the kinematics decoupling of mobile manipulator is important, especially the control methods based on neural network. To solve the deficiency of neural network such as decision of structure and adjustment of parameters in hidden-unit, genetic algorithm based on RBF neural network is presented to deal with kinematics decoupling of mobile manipulator. The centers and widths of hidden layer and the weights of the output layer are coded into one chromosome. It strengthens the cooperation between the hidden layer and the output layer, and avoids the risk of getting stuck into a local minimum. RBF neural network using genetic algorithm is established for kinematics decoupling which brought by coordinated motion between the manipulator and mobile platform of mobile robot system. The experimental results show the method reasonable and effective.

Published in:

Information Technology and Computer Science, 2009. ITCS 2009. International Conference on  (Volume:2 )

Date of Conference:

25-26 July 2009