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Three-dimensional neural net for learning visuomotor coordination of a robot arm

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3 Author(s)
Martinetz, T.M. ; Dept. of Phys., Illinois Univ., Urbana, IL, USA ; Ritter, H.J. ; Schulten, K.J.

An extension of T. Kohonen's (1982) self-organizing mapping algorithm together with an error-correction scheme based on the Widrow-Hoff learning rule is applied to develop a learning algorithm for the visuomotor coordination of a simulated robot arm. Learning occurs by a sequence of trial movements without the need for an external teacher. Using input signals from a pair of cameras, the closed robot arm system is able to reduce its positioning error to about 0.3% of the linear dimensions of its work space. This is achieved by choosing the connectivity of a three-dimensional lattice consisting of the units of the neural net

Published in:

Neural Networks, IEEE Transactions on  (Volume:1 ,  Issue: 1 )

Date of Publication:

Mar 1990

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