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Point Cloud Based Three-Dimensional Reconstruction and Identification of Initial Welding Position

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Transactions on Intelligent Welding Manufacturing

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

Abstract

Initial welding position guidance is necessary for vision-based intelligentized robotic welding. In this paper, we proposed a point cloud based approach to recognize working environment and locate welding initial position using laser stripe sensor. Calibrated laser sensor can achieve high accuracy in transforming from image coordinate system to camera coordinate system and to robot tool coordinate system with hand-eye calibration. Linear feature based image processing algorithm is developed to extract the position of laser stripe center in subpixel-level accuracy; then trajectory-queue based interpolation is implemented to convert down-sampled laser points to robot base coordinate system in real-time scanning. Identification of workpiece is implemented by segmenting workpieces from the point cloud data in the image. Before segmentation, KD-Tree based background model is constructed to filter out background points; then RANSAC fitting procedure rejects outliers and fits the correct workpiece plane model; and the welding initial position can be found along the weld seam which is the intersection of fitted planes. In verification experiment, workpiece planes and welding initial position can be correctly recognized despite the presence of abnormal noises.

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References

  1. Chen SB (2015) On intelligentized welding manufacturing. In: Robotic welding, intelligence and automation. Springer, Berlin, pp 3–34

    Google Scholar 

  2. Zhu ZY, Lin T, Piao YJ et al (2005) Recognition of the initial position of weld based on the image pattern match technology for welding robot. Int J Adv Manuf Technol 26(7–8):784–788

    Article  Google Scholar 

  3. Chen XZ, Chen SB (2010) The autonomous detection and guiding of start welding position for arc welding robot. Ind Robot 37(1):70–78

    Article  Google Scholar 

  4. Dinham M, Fang G (2013) Autonomous weld seam identification and localisation using eye-in-hand stereo vision for robotic arc welding. Robot Comput Integr Manuf 29:288–301

    Article  Google Scholar 

  5. Xu Y, Yu H, Zhong J et al (2012) Real-time seam tracking control technology during welding robot GTAW process based on passive vision sensor. J Mater Process Technol 212(8):1654–1662

    Article  Google Scholar 

  6. Li X, Ge S, Khyam MO et al (2017) Automatic welding seam tracking and identification. IEEE Trans Ind Electron 99:1

    Google Scholar 

  7. Ding Y, Huang W, Kovacevic R (2016) An on-line shape-matching weld seam tracking system. Robot Comput Integ Manuf 42:103–112

    Article  Google Scholar 

  8. Huynh DQ, Owens RA, Hartmann P (1999) Calibrating a structured light stripe system: a novel approach. Int J Comput Vision 33(1):73–86

    Article  Google Scholar 

  9. Wengert C, Reeff M, Cattin PC, et al (2006) Fully automatic endoscope calibration for intraoperative use. Bildverarbeitung für die Medizin, 419–423

    Google Scholar 

  10. Forest J, Salvi J, Cabruja E, et al (2004) Laser stripe peak detector for 3D scanners. A FIR filter approach. In: Proceedings of the 17th international conference on pattern recognition, IEEE, pp. 646–649

    Google Scholar 

  11. Du J, Xiong W, Chen W, et al (2015) Robust laser stripe extraction using ridge segmentation and region ranking for 3D reconstruction of reflective and uneven surface. In: IEEE International conference on image processing, IEEE, pp 4912–4916

    Google Scholar 

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Acknowledgements

This work is partly supported by the National Natural Science Foundation of China (51405298 and 51575349), Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration, the State Key Laboratory of Smart Manufacturing for Special Vehicles and Transmission System (GZ2016KF002), the Development Fund Project of the Science and Technology Committee of Qingpu District and the National High Technology Research and Development Program 863 (2015AA043102).

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Correspondence to Yanling Xu .

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© 2018 Springer Nature Singapore Pte Ltd.

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Zhang, L., Xu, Y., Du, S., Zhao, W., Hou, Z., Chen, S. (2018). Point Cloud Based Three-Dimensional Reconstruction and Identification of Initial Welding Position. In: Chen, S., Zhang, Y., Feng, Z. (eds) Transactions on Intelligent Welding Manufacturing. Transactions on Intelligent Welding Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-10-8330-3_4

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  • DOI: https://doi.org/10.1007/978-981-10-8330-3_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8329-7

  • Online ISBN: 978-981-10-8330-3

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