“ART-1 Simulator” for Identification of Objects in Robotics

Abstract

This paper presents an algorithm for effective learning of the Adaptive Resonance Theory (ART-1) artificial neural network and shows the convenience of applying this network for object identification, on the basis of which the zero version of the "ART-1 Simulator" software was developed for new generation recognition systems which are used today in the control of intelligent industrial robot based on CCD camera involvement. The parameters of the ART-1 structure are in accordance with captured images and learning procedure, adopted for identification of objects in robotic environment.