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Enhancing flexibility of vision‐based robots using an artificial neural network approach

Siang Kok Sim (School of Mechanical Production Engineering, Nanyang Technological University, Singapore)
Ming Yeong Teo (School of Mechanical Production Engineering, Nanyang Technological University, Singapore)

Integrated Manufacturing Systems

ISSN: 0957-6061

Article publication date: 1 February 1997

Abstract

Describes work based on the hypothesis that the use of artificial neural networks can imbue vision‐based robots with the ability to learn about their environment and hence enhance their competence and flexibility. The Neocognitron neural network provides the vision‐based robot with the capability of learning about its environment through training to recognize certain objects. The Neocognitron network is selected because of its ability to tolerate translational, rotational and scaling invariance in the input pattern of objects. Presents results which support the use of Neocognitron in enhancing the flexibility of vision‐based robots.

Keywords

Citation

Kok Sim, S. and Yeong Teo, M. (1997), "Enhancing flexibility of vision‐based robots using an artificial neural network approach", Integrated Manufacturing Systems, Vol. 8 No. 1, pp. 43-49. https://doi.org/10.1108/09576069710158790

Publisher

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MCB UP Ltd

Copyright © 1997, MCB UP Limited