Year: 2025
Type: article
Abstract: This project explores the differentiation of AA, D, and 9V batteries using RoBatt, an Epson VT6 robot integrated with YOLOv8, a state-of-the-art object detection model. The robotic arm is controlled to detect and sort batteries using parameters modeled by the YOLO v8. The use of YOLO v8 allows such detection and classification to occur instantly without compromising the efficiency of the sorting process. Additionally, to improve its operational capabilities, RoBatt is equipped with electromagnetic gripper for the purpose of attracting batteries. The result of the study shows viability to use deep learning and robotics for sorting batteries, and it can be done for commercial or recycling purposes. This integration presents a novel concept for battery waste management and recycling system.
Authors: Faizan Mistry, Judhi Prasetyo
Institution: Middlesex University Dubai
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
Funder: Middlesex University
OpenAlex ID: W4409103448