Vol.12, No.4, November 2023.                                                                                                                                                                               ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

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


Jakub Müller, Tomáš Broum, Miroslav Malaga


© 2023 Miroslav Malaga, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 12, Issue 4, Pages 1929-1938, ISSN 2217-8309, DOI: 10.18421/TEM124-02, November 2023.


Received: 25 July 2023.

Revised:   16 October 2023.
Accepted: 02 November 2023.
Published: 27 November 2023.




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'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.


Keywords –Collaborative robots, computer vision system, reliability, industry 4.0, experimental study.



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