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Product Classification Using Neural Network at Industry Robotic Line Cover

Abstract

The article describes a possible way of implementing a neural network in recognizing the shape and position of the products in the production process. The neural network is designed as a multilayer perceptron (MLP), and the whole system is implemented in a form of attachment to robotic arm, where the primary task of neural network is to distinguish a position of product. The neural network is trained like a classifier and outputs are used to control the robot. The advantage of the solution is a high degree of reliability of product positioning under different lighting conditions.

DOI: https://doi.org/10.2478/rput-2019-0026 | Journal eISSN: 1338-0532 | Journal ISSN: 1336-1589
Language: English
Page range: 55 - 63
Submitted on: Aug 27, 2019
Accepted on: Sep 24, 2019
Published online: Dec 16, 2019
Published in print: Sep 1, 2019
Published by: Slovak University of Technology in Bratislava
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2019 Igor Halenár, Gabriela Križanová, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.