DocumentCode
2933040
Title
Solutions of kinematics of robot manipulators using a Kohonen self-organizing neural network
Author
Wang, Dali ; Zilouchian, Ali
Author_Institution
Dept. of Electr. Eng., Florida Atlantic Univ., Boca Raton, FL, USA
fYear
1997
fDate
16-18 Jul 1997
Firstpage
251
Lastpage
255
Abstract
Kohonen self-organizing neural network is used to solve the forward kinematics problems of robot manipulators. Through competition learning, neurons learn their distribution in the training phase. In sequel, the nonlinear mapping has been obtained by proper calibration of training results. The proposed method is based on the unsupervised learning which does not rely on the knowledge of process model information. Simulation results have effectiveness of the proposed method for a two degree planar robot manipulator
Keywords
manipulator kinematics; self-organising feature maps; unsupervised learning; Kohonen self-organizing neural network; calibration; competition learning; forward kinematics problems; nonlinear mapping; two degree planar robot manipulator; unsupervised learning; Calibration; End effectors; Kinematics; Manipulators; Neural networks; Neurons; Orbital robotics; Organizing; Robots; Supervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 1997. Proceedings of the 1997 IEEE International Symposium on
Conference_Location
Istanbul
ISSN
2158-9860
Print_ISBN
0-7803-4116-3
Type
conf
DOI
10.1109/ISIC.1997.626466
Filename
626466
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