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

Jakub Müller Müller, Tomáš Broum, Miroslav Malaga

Year
2023
Citations
3
Access
Open access

Abstract

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

Machine visionWorkspaceArtificial intelligenceReliability (semiconductor)RobotComputer scienceSMT placement equipmentComputer visionObject (grammar)Human–computer interaction

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