Vision-based construction robot for real-time automated welding with human-robot interaction

Doyun Lee, Kevin Han

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The construction industry is a major consumer of steel, with welding being a crucial aspect of steel fabrication. However, a shortage of welders has emerged as a significant issue. Therefore, the ultimate goal of this study is to develop a fully automated mobile robotic welding system. The preliminary paper presented a method for the automatic detection and alignment of various welding joints. Building on this, this paper proposes a real-time automated welding system capable of path planning and tracking for two butt joints using visual data. Given the precision required in welding, two robotic operations were devised: one for following a trajectory based on real-time image data, and another for welding guided by laser-scanned data. Additionally, human-robot interaction is proposed for path planning in cases where deep learning-based joint detection fails. The automated robotic welding was performed to test the performance of the proposed system, demonstrating its effectiveness and accuracy.

Original languageEnglish
Article number105782
JournalAutomation in Construction
Volume168
DOIs
StatePublished - Dec 1 2024

Scopus Subject Areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

Keywords

  • Human-robot interaction
  • Path planning
  • Path tracking
  • Robotic arm control
  • Robotic integration
  • Robotic welding
  • Welding joint dataset

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