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Research on the Calibration Method of Welding Inspection Robot's Binocular Vision

Ping An, Yongxiang Jiang, Hongchang Sun
Frontiers in Sustainable Development, (2026), Vol.6, No.2, pp.87-92
Published: February 28, 2026
DOI: 10.54691/7embhs98
PDF: Download Full Text PDF
Abstract

In the context of intelligent manufacturing, the automation and intelligent upgrading of welding inspection have become core requirements in industrial fields. Traditional manual inspection faces challenges such as low accuracy, poor efficiency, and difficulties in adapting to hazardous environments. The integration of machine vision and welding robots provides a key solution to these issues, with precise calibration of binocular vision systems serving as the core prerequisite for this integration. This study systematically investigates the calibration of binocular vision systems in welding inspection robots: it completes the resolution of camera internal and external parameters; experimental verification using MATLAB calibration tools demonstrates a reprojected error of 0.06 pixels, with actual measurement errors ≤0.02mm and a standard deviation of 0.0073mm, indicating high calibration accuracy. The research provides a complete and feasible calibration technical solution that enables precise 3D positioning of welds, enhances the automation and intelligence of welding inspection, and can be extended to various industrial inspection scenarios, demonstrating strong engineering application value.

Keywords: Welding Inspection Robot; Binocular Vision System; System Calibration; Image Preprocessing; Coordinate System Transformation.
APA Citation: Ping An, Yongxiang Jiang, Hongchang Sun (2026). Research on the Calibration Method of Welding Inspection Robot's Binocular Vision. Frontiers in Sustainable Development, 6(2), 87-92. https://doi.org/10.54691/7embhs98

References

  1. Yin Wenqian. Research on Improving Calibration Accuracy to Enhance Barcode Recognition Efficiency [J]. Automation Technology and Application, 2023,42(5):12-18.
  2. Chen H. High-precision measurement applications of binocular vision based on OpenCV and VS2017 [J]. Computer Engineering and Design, 2022,43(8):2234-2240.
  3. Han B. Complex workpiece recognition algorithm based on fusion neural network and binocular vision[J]. Journal of Mechanical Engineering, 2024,50(3):156-163.
  4. Shen H K, Li W, Zhang Y. Adaptive optimization calibration algorithm for laser and binocular vision fusion[J]. Optics and Lasers in Engineering, 2025, 182: 108456.
  5. Wang J, Chen T, Wang Y. Coordinate transformation technology in binocular vision calibration[J]. IEEE Transactions on Instrumentation and Measurement, 2024, 73: 1-10.
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