Vo Thu Ha1, Than Thi Thuong1, and Vo Thanh Ha This email address is being protected from spambots. You need JavaScript enabled to view it.2,3

1Faculty of Electrical Engineering, University of Economics - Technology for Industries, Vietnam
2Faculty of Electrical and Electronic Engineering University of Transport and Communications, Vietnam
3University of Transport and Communications, No. 3 Cau Giay Street, Lang Thuong Ward, Dong Da District, Hanoi, Vietnam


Received: July 7, 2022
Accepted: November 5, 2022
Publication Date: December 19, 2022

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202309_26(9).0014  


The paper has presented the control and development of an intelligent garbage sorting system with a robot arm. This system consists of a machine vision block, a 6DOF robot manipulator, and a control unit for sorting garbage based on analytical images. YOLOv4 software will be identified the object by the neural network. This method is used for detecting and image recognition of different sizes and types of waste, such as paper-based garbage, metal garbage, and plastic garbage. The results of offline testing on a database of more than 600 untrained images show that the trained model has an average accuracy of about 98.43% for classifying different types of garbage.

Keywords: Waste Sorting, Robotic Arm, YOLO, Machine Vision, 6DOF


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