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A vision-based method for narrow weld trajectory recognition of arc welding robots

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Abstract

With the rapid development of the manufacturing industry, the demand for autonomy of welding robots is also improving. To improve the autonomy of welding robots, the first problem to be solved is the identification and positioning of the weld seam. In general, it is a challenge to extract narrow weld seams in workpieces with characteristics such as no texture, smoothness, and strong reflection using passive vision sensors. In this paper, we propose a vision-based method for the 2-dimensional (2D) and 3-dimensional (3D) detection and localization of narrow weld seams to improve the sensing capability and automation of welding robot systems. The method enhances narrow weld seam features by adjusting the image grayscale expectation at the time of shooting to achieve weld seam recognition within the field of view. Then, the point cloud of the weld area is obtained using the triangulation technique of stereo vision to realize weld seam localization. Finally, the calculated weld trajectory is matched with the trajectory extracted from the workpiece model to realize recognition of welding tasks. Experiments were conducted on ferrous and galvanized workpieces, and the final experimental results demonstrate the effectiveness of the proposed method.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant No.U20A20201, in part by Shandong Provincial Key Research and Development Program (Major Scientific and Technological Innovation Project) under Grant No.2019JZZY010441, and in part by Project funded by China Postdoctoral Science Foundation (Grant No.2021M691927).

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Authors and Affiliations

  1. Center for Robotics, School of Control Science and Engineering, Shandong University, Jinshi Road, Jinan, 250061, Shandong, China

    Weihua Fang, Xiaolong Xu & Xincheng Tian

  2. Engineering Research Center of Intelligent Unmanned System, Ministry of Education, Jinshi Road, Jinan, 250061, Shandong, China

    Weihua Fang, Xiaolong Xu & Xincheng Tian

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  1. Weihua Fang
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  2. Xiaolong Xu
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  3. Xincheng Tian
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Contributions

Weihua Fang conceived the presented idea, developed the theory, and carried out the experiments. Xiaolong Xu and Xincheng Tian were involved in planning and supervised the work. All the authors discussed the results and contributed to the final manuscript.

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Correspondence to Xincheng Tian.

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Fang, W., Xu, X. & Tian, X. A vision-based method for narrow weld trajectory recognition of arc welding robots. Int J Adv Manuf Technol 121, 8039–8050 (2022). https://doi.org/10.1007/s00170-022-09804-x

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