DocumentCode :
2755552
Title :
A hierarchy of self-organized multiresolution artificial neural networks for robotic control
Author :
D´Eleuterio, G.M.T.
fYear :
1991
fDate :
8-14 Jul 1991
Abstract :
Summary form only given, as follows. A robotic control system based upon the CMAC, and an enhancement to this architecture using a hierarchy of CMAC neural networks, are discussed. The overlapping input domain cells of each of the layers in the hierarchy are organized using a simple Kohonen network. Using this novel approach, the manipulator input domain has been discretized into cells that have varying placement and size as well as retaining coarse coding generalization. This scheme was evaluated using a computer simulation of a robotic system and has shown significant improvement in the network´s overall performance
Keywords :
neural nets; robots; self-adjusting systems; CMAC; Kohonen network; coarse coding generalization; hierarchy; overlapping input domain cells; robotic control; self adjusting systems; self-organized multiresolution artificial neural networks; Aerospace control; Artificial neural networks; Computer simulation; Control systems; Manipulators; Robot control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
Type :
conf
DOI :
10.1109/IJCNN.1991.155680
Filename :
155680
Link To Document :
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