UIArm I: Development of a Low-Cost and Modular 4-DOF Robotic Arm for Sorting Plastic Bottles from Waste Stream

  • Enoch M. Adediran
  • , David A. Fadare
  • , Ayodeji Falana
  • , Rasaq A. Kazeem
  • , Omolayo M. Ikumapayi
  • , Adebayo S. Adedayo
  • , Adedotun O. Adetunla
  • , Umeh J. Ifebunandu
  • , Dorcas A. Fadare
  • , Elisabeta S. Olarinde

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The study presents the development of an accessible, reliable, 3D printable, low-cost, and modular 4 degrees-of-freedom robotic arm for the automated sorting of plastic bottles from the waste stream. The UIArm I robot arm was designed based on the modification of an open-source Thor Robot model using Free-CAD with the components 3D printed using PLA and PETG. The forward kinematics was obtained by Denavit-Hartenberg (DH) method, while the analytical method was used for the inverse kinematics. The electrical components include stepper motors, servo motors, motor drivers, a printed circuit board (PCB), an Arduino Mega microprocessor, a light source for illumination, and a PC with a webcam. Python was used for programming the PC and C# for the Arduino microprocessor. TensorFlow, an end-to-end open-source, machine learning platform was used to develop the object detection algorithm based on a deep neural network. The object detection model achieved an accuracy of 91% for Pepsi plastic bottles which formed the bulk of training images. Other types of plastic bottles were detected with an 85% accuracy. The study has demonstrated the viability of a locally developed robotic arm for the automated sorting of plastic bottles.

Original languageEnglish
Pages (from-to)97-103
Number of pages7
JournalJournal Europeen des Systemes Automatises
Volume56
Issue number1
DOIs
Publication statusPublished - Feb 2023
Externally publishedYes

Keywords

  • complex backgrounds
  • deep learning
  • garbage sorting
  • machine vision
  • robotic grasping

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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