Product Classification Using Neural Network at Industry Robotic Line

Halenár Igor () and Križanová Gabriela ()
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Halenár Igor: Slovak University of Technology in Bratislava, Faculty of Materials Science and Technology in Trnava, Institute of Applied Informatics, Automation and Mechatronics, Ulica Jána Bottu Č. 2781/25, 917 24Trnava, Slovak Republic
Križanová Gabriela: Slovak University of Technology in Bratislava, Faculty of Materials Science and Technology in Trnava, Institute of Applied Informatics, Automation and Mechatronics, Ulica Jána Bottu Č. 2781/25, 917 24Trnava, Slovak Republic

Research Papers Faculty of Materials Science and Technology Slovak University of Technology, 2019, vol. 27, issue 45, 55-63

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.

Keywords: Neural network; Deep learning; Detection; Robot (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:repfms:v:27:y:2019:i:45:p:55-63:n:8

DOI: 10.2478/rput-2019-0026

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