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Transactions on Intelligent Welding Manufacturing pp 61–86Cite as

Vision-Based Seam Tracking in Robotic Welding: A Review of Recent Research

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Part of the book series: Transactions on Intelligent Welding Manufacturing ((TRINWM))

Abstract

Robotic welding is widely used in industrial automation, and weld seam tracking is key to the robotic welding and needs to be solved urgently. Because of high precision and adaptability, vision-based seam tracking has become the most widely used technology in weld seam tracking. Researches on vision-based seam tracking have been conducted by many scholars and progressive results have been obtained. Aimed at key problems of seam tracking, this paper summarizes the relevant research work in recent years, especially the application of active vision and passive vision. This paper focuses on the advantages and defects of these two typical methods and discusses recent outstanding progress on seam tracking techniques. In addition, the possibility of the composite vision method of active vision and passive vision in tracking is also discussed, and development directions of intelligent weld seam tracking technology are prospected.

These authors contributed equally to this work.

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Acknowledgements

This work is partly supported by the National Natural Science Foundation of China (61973213), and the Shanghai Natural Science Foundation (18ZR1421500).

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Authors and Affiliations

  1. School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, 19104, USA

    Ziheng Wang

  2. Intelligentized Robotic Welding Technology Laboratory, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Yanling Xu

  3. Shanghai Key Laboratory of Materials Laser Processing and Modification, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Yanling Xu

Authors
  1. Ziheng Wang
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  2. Yanling Xu
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Correspondence to Yanling Xu .

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Editors and Affiliations

  1. Shanghai Jiao Tong University, Shanghai, China

    Shanben Chen

  2. Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY, USA

    Yuming Zhang

  3. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Zhili Feng

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Wang, Z., Xu, Y. (2020). Vision-Based Seam Tracking in Robotic Welding: A Review of Recent Research. In: Chen, S., Zhang, Y., Feng, Z. (eds) Transactions on Intelligent Welding Manufacturing. Transactions on Intelligent Welding Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-13-8192-8_3

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