Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Intelligent Dynamic Identification of Industrial Productsin a Robotic Workplace

Version 1 : Received: 2 February 2021 / Approved: 4 February 2021 / Online: 4 February 2021 (12:12:30 CET)

A peer-reviewed article of this Preprint also exists.

Vachálek, J.; Šišmišová, D.; Vašek, P.; Rybář, J.; Slovák, J.; Šimovec, M. Intelligent Dynamic Identification Technique of Industrial Products in a Robotic Workplace. Sensors 2021, 21, 1797. Vachálek, J.; Šišmišová, D.; Vašek, P.; Rybář, J.; Slovák, J.; Šimovec, M. Intelligent Dynamic Identification Technique of Industrial Products in a Robotic Workplace. Sensors 2021, 21, 1797.

Journal reference: Sensors 2021, 21, 1797
DOI: 10.3390/s21051797

Abstract

The article deals with aspects of identifying industrial products in motion based on their color. An automated robotic workplace with conveyor belt, robot and industry color sensor is created for this purpose. Measured data are processed in a database and then statistically evaluated in form of standard uncertainties of type A and B, in order to obtain combined standard uncertainties results. Based on the acquired data, control charts of RGB color components for identified products are created. Influence of product speed on the measuring process identification and process stability is monitored. In case of identification uncertainty i.e. measured values are outside the limits of control charts, the K-nearest neighbor machine learning algorithm is used. This algorithm, based on the Euclidean distances to the classified value, estimates its most accurate iteration. This results into the comprehensive system for identification of product moving on conveyor belt, where based on the data collection and statistical analysis using machine learning, industry usage reliability is demonstrated.

Subject Areas

measurement; uncertainties; calibration; control charts; machine learning; color sensor; identification; robotics; production systems; Siemens Tecnomatix

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