Paper
29 October 1996 Neural network system for purposeful behavior based on foveal visual preprocessor
Alexander V. Golovan, Natalia A. Shevtsova, Arkadi A. Klepatch
Author Affiliations +
Abstract
Biologically plausible model of the system with an adaptive behavior in a priori environment and resistant to impairment has been developed. The system consists of input, learning, and output subsystems. The first subsystems classifies input patterns presented as n-dimensional vectors in accordance with some associative rule. The second one being a neural network determines adaptive responses of the system to input patterns. Arranged neural groups coding possible input patterns and appropriate output responses are formed during learning by means of negative reinforcement. Output subsystem maps a neural network activity into the system behavior in the environment. The system developed has been studied by computer simulation imitating a collision-free motion of a mobile robot. After some learning period the system 'moves' along a road without collisions. It is shown that in spite of impairment of some neural network elements the system functions reliably after relearning. Foveal visual preprocessor model developed earlier has been tested to form a kind of visual input to the system.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexander V. Golovan, Natalia A. Shevtsova, and Arkadi A. Klepatch "Neural network system for purposeful behavior based on foveal visual preprocessor", Proc. SPIE 2904, Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling, (29 October 1996); https://doi.org/10.1117/12.256283
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KEYWORDS
Neural networks

Neurons

Visualization

Computer simulations

Computing systems

Control systems

Roads

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