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Received: 2005-06-20

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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.4 P.525-529

http://doi.org/10.1631/jzus.2006.A0525


Wavelet network solution for the inverse kinematics problem in robotic manipulator


Author(s):  Chen Hua, Chen Wei-shan, Xie Tao

Affiliation(s):  School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China

Corresponding email(s):   chenhua202@126.com

Key Words:  Inverse kinematics problem, Robotic manipulator, Wavelet network


Chen Hua, Chen Wei-shan, Xie Tao. Wavelet network solution for the inverse kinematics problem in robotic manipulator[J]. Journal of Zhejiang University Science A, 2006, 7(4): 525-529.

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author="Chen Hua, Chen Wei-shan, Xie Tao",
journal="Journal of Zhejiang University Science A",
volume="7",
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pages="525-529",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A0525"
}

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%A Chen Hua
%A Chen Wei-shan
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A0525

TY - JOUR
T1 - Wavelet network solution for the inverse kinematics problem in robotic manipulator
A1 - Chen Hua
A1 - Chen Wei-shan
A1 - Xie Tao
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 4
SP - 525
EP - 529
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Y1 - 2006
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2006.A0525


Abstract: 
wavelet network, a class of neural network consisting of wavelets, is proposed to solve the inverse kinematics problem in robotic manipulator. A wavelet network suitable for dealing with multi-input and multi-output system is constructed. The network is optimized by reducing the number of wavelets handling large dimension problem according to the sample data. The algorithms for sparseness analysis of input data and fitting wavelets to the output data with orthogonal method are introduced. Then Levenberg-Marquardt algorithm is used to train the network. Simulation results showed that this method is capable of solving the inverse kinematics problem for PUMA560.

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

Reference

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[2] Chen, X.S., Chen, Z.L., Xie, T., 2002. An accurate solution to the inverse kinematic problem of a robot manipulator based on the neural network. Chinese Journal of Robot, 24(2):130-133 (in Chinese).

[3] Guez, A., Ahmad, Z., 1988. Solution to the Inverse Kinematics Problem in Robotics by Neural Networks. IEEE International Conference on Neural Network, San Diego, California, 2:617-621.

[4] Guo, J., Cherkassky, V., 1989. A Solution to the Inverse Kinematic Problem in Robotics Using Neural Network Processing. IEEE International Conference on Neural Network, Washington D.C., 2:299-304.

[5] Mavroidis, C., Ouezdou, F.B., Bidaud, P., 1994. Inverse kinematics of six degree of freedom ‘general’ and ‘special’ manipulators using symbolic computation. Robotica, 12(5):421-430.

[6] Raghavan, M., Roth, B., 1995. Solving polynomial systems for the kinematics analysis and synthesis of mechanisms and robot manipulator. Journal of Mechanical Design, 117:71-79.

[7] Sun, W., Wang, Y., Mao, J., 2002. Using Wavelet Network for Identifying the Model of Robot Manipulator. Proceedings of the 4th World Congress on Intelligent Control and Automation, 2:1634-1638.

[8] Wu, Y.C., Hsieh, N.H., Chen, Z.R., 2003. The Application of Intelligent Algorithm Principle on Robot Exercise. Proceedings of the 2003 IEEE/ASME International Conference on Advanced Inteligent Mechatronics (AIM 2003), p.371-376.

[9] Zhang, Q.H., 1997. Using wavelet network in nonparametric estimation. IEEE Trans. Neural Network, 8(2):227-236.

[10] Zhang, Q., Benveniste, A., 1992. Wavelet networks. IEEE Trans. Neural Networks, 3(6):889-898.

[11] Zhang, W., Ding, Q., 1997. Inverse kinematics for a 6 DOF manipulator based on neural network. Transactions of Nanjing University of Aeronautics and Astronautics, 14(1):73-76.

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