A Review of Machine Vision Systems for Real-Time Weld Seam Tracking in Robotic Environments

EasyChair Preprint 11767

Abstract

This paper presents a comprehensive review of machine vision systems designed for real-time weld seam tracking in robotic environments. Weld seam tracking is a critical aspect of robotic welding processes, ensuring precise and efficient performance. The review covers various machine vision techniques, including image processing algorithms, sensors, and tracking methodologies employed in the context of welding applications. The analysis encompasses both traditional and state-of-the-art approaches, highlighting their strengths, limitations, and comparative performance. Insights from this review aim to contribute to the advancement of machine vision systems in enhancing the accuracy and reliability of weld seam tracking in dynamic and challenging robotic environments.

Keyphrases: SEAM, Tracking, weld

@booklet{EasyChair:11767,
  author    = {Jane Smith and Chen Liu},
  title     = {A Review of Machine Vision Systems for Real-Time Weld Seam Tracking in Robotic Environments},
  howpublished = {EasyChair Preprint 11767},
  year      = {EasyChair, 2024}}