Autonomous robot behavior based on neural networks (CROSBI ID 464568)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Grolinger, Katarina ; Jerbić, Bojan ; Vranješ, Božo
engleski
Autonomous robot behavior based on neural networks
The purpose of autonomous robot is to solve various tasks while adapting its behavior to the variable environment, expecting it is able to navigate much like a human would, including handling uncertain and unexpected obstacles. To achieve this the robot has to be able to find solution in unknown situations, to learn experienced knowledge, that means action procedure together with corresponding knowledge on the work space structure, and to recognize working environment. The planing of the intelligent robot behavior presented in this paper implements the reinforcement learning based on strategic and random attempts for finding solution and neural network approach for memorizing and recognizing work space structure (structural assignment problem). Some of the well known neural networks based on unsupervised learning are considered with regard to the structural assignment problem. The adaptive fuzzy shadowed (AFS) neural network is developed. It has the additional shadowed hidden layer, specific learning rule and initialization phase. The developed neural network combines advantages of networks based on the Adaptive Resonance Theory and using shadowed hidden layer provides ability to recognize lightly translated or rotated obstacles in any direction.
robot; learning; neural networks; intelligence
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Podaci o prilogu
2038-2046-x.
1997.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of Applications and Science of Artificial Neural Networks III
Rogers, Steven K.
Orlando (FL): SPIE
Podaci o skupu
Wavelets and Neural Networks
predavanje
21.04.1997-24.04.1997
Orlando (FL), Sjedinjene Američke Države