Design and development of an automated robotic system for classification and sorting using machine vision
DOI:
https://doi.org/10.15282/mekatronika.v8i1.13367Keywords:
Automation, Image Processing, Industry 4.0, Machine Vision, Robotic arm, YOLOv11Abstract
The growing increase in the demand for goods has pushed automation to the forefront of industrial innovation. However, most manufacturing industries still rely on traditional automated means of production, which are slow and inefficient for handling concurrent increases in production. In this study, the design and development of an automated robotic system that integrates a machine vision algorithm through a webcam to detect and classify objects on a conveyor system based on two classes is presented. A 2-degree-of-freedom (DOF) robotic arm controlled by an ESP32 sorts the product into the designated bins based on a specified servo angle. The machine vision algorithm achieved a mean average precision (mAP) of 99.1%. The results of the overall robotic system setup for classification and sorting produced an accuracy of 94% and 92%, respectively. This is a robotic system framework that is geared toward Industry 4.0. Future work will incorporate more classes and optimisation techniques to further improve the system’s accuracy.
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