Evaluating the Reliability of a Machine Vision System for Collaborative Robots: An Experimental Study in the Industry 4.0 Environment

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23210%2F23%3A43970229" target="_blank" >RIV/49777513:23210/23:43970229 - isvavai.cz</a>

Result on the web

<a href="https://www.temjournal.com/content/124/TEMJournalNovember2023_1929_1938.pdf" target="_blank" >https://www.temjournal.com/content/124/TEMJournalNovember2023_1929_1938.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18421/TEM124-02" target="_blank" >10.18421/TEM124-02</a>

Result language

angličtina

Original language name

Evaluating the Reliability of a Machine Vision System for Collaborative Robots: An Experimental Study in the Industry 4.0 Environment

Original language description

This research evaluates the reliability of a machine vision system connected to a collaborative robot. In recent scientific papers, the authors have focused on machine vision itself, machine vision systems and related theory in general, along with machine learning methods, and image processing itself. However, there seems to be a missing link between these topics and the industrial robot&apos;s accuracy in basic tasks when utilizing machine vision. The experiments conducted, took place within an Industry 4.0 laboratory, where 3D-printed objects were utilized as test subjects. The collaborative robot, equipped with machine vision, performed tasks such as object removal and stacking. The evaluation focused on the success rate of object assembly and grasping. The paper discusses the integration of machine vision technology, previous research on reliability, and the use of a 2D camera for the collaborative robot. The findings contribute to understanding the potential of machine vision in enhancing efficiency and precision in collaborative robot workspaces.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS

ISSN

2217-8309

e-ISSN

2217-8333

Volume of the periodical

12

Issue of the periodical within the volume

4

Country of publishing house

RS - THE REPUBLIC OF SERBIA

Number of pages

10

Pages from-to

1929-1938

UT code for WoS article

001111557300065

EID of the result in the Scopus database

2-s2.0-85179073337