@inproceedings{0bfd6fd162ad4f149bbb791f63ca8bd8,
title = "Automated Grinding and Polishing System for Carbide Spots",
abstract = "This study presents a robotic automated polishing and grinding system for metals based on a depth camera. The system captures images of the metal component using a depth camera and utilizes visual recognition to identify carbide spot defects. Simultaneously, the coordinates of each carbide spot in the 3D point cloud are transformed into the robotic arm's coordinate system using perspective transformation, ensuring stable conversion of carbide spots into arm coordinates. This guides the robotic arm to perform precise grinding operations, ensuring accurate defect repair or removal and achieving automated robotic polishing. We detected 903 carbide spots across 100 metal components, with an average maximum error of 0.95 millimeters. The system boasts high precision and efficiency, with experimental results demonstrating a welding spots recognition accuracy of up to 99%, and a margin of less than 3 millimeters. This system not only enhances production efficiency and quality but also realizes the goal of intelligent manufacturing.",
keywords = "Defect detection, Image recognition, Intelligent manufacturing, Perspective transformation, Robotic arm",
author = "Chou, {Young Ching} and Lee, {Ming Lun} and Chang, {Chun Hao} and Lin, {Cheng Kuan} and Tseng, {Yu Chee}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 3rd International Conference on Electronic Information Engineering and Computer Science, EIECS 2023 ; Conference date: 22-09-2023 Through 24-09-2023",
year = "2023",
doi = "10.1109/EIECS59936.2023.10434286",
language = "English",
series = "2023 3rd International Conference on Electronic Information Engineering and Computer Science, EIECS 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "612--616",
booktitle = "2023 3rd International Conference on Electronic Information Engineering and Computer Science, EIECS 2023",
address = "美國",
}