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Product Classification Using Neural Network at Industry Robotic Line

Author

Listed:
  • Halenár Igor
  • 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 24 Trnava, Slovak Republic)

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.

Suggested Citation

  • Halenár Igor & Križanová Gabriela, 2019. "Product Classification Using Neural Network at Industry Robotic Line," Research Papers Faculty of Materials Science and Technology Slovak University of Technology, Sciendo, vol. 27(45), pages 55-63, September.
    • Handle: RePEc:vrs:repfms:v:27:y:2019:i:45:p:55-63:n:8
    DOI: 10.2478/rput-2019-0026
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