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
Link To Document :
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