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HU Jiacheng, YU Shuangfei, ZHANG Tao, GUAN Yisheng, ZHU Haifei. Determination of welding torch space pose based on local point cloud of weld path points[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2024, 45(4): 86-92. DOI: 10.12073/j.hjxb.20230406002
Citation: HU Jiacheng, YU Shuangfei, ZHANG Tao, GUAN Yisheng, ZHU Haifei. Determination of welding torch space pose based on local point cloud of weld path points[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2024, 45(4): 86-92. DOI: 10.12073/j.hjxb.20230406002

Determination of welding torch space pose based on local point cloud of weld path points

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  • Received Date: April 05, 2023
  • Available Online: March 03, 2024
  • In view of the current research on robot welding of workpieces with uncertain geometric and positional information based on 3D visual sensing, the method for determining the spatial posture of the welding torch at the welding path point is highly targeted and has high limitations. A method of determining welding torch space pose based on local point cloud of weld path points was proposed. Firstly, the spatial pose parameter model of welding torch is described, and then the local point cloud at the weld path point is obtained by considering the the sensor front-mounted distance to determine the minimum search radius of kd-tree, and the deflection plane and inclined plane of welding torch at the path point are gradually determined, so as to determine the non-collision space pose between the welding torch and the workpiece at the weld path points. The results show that this method has strong adaptability and good effectiveness. Due to the surface quality of point clouds, there is certain fluctuation in the attitude determination results compared with the real attitude, but it can be smoothed to meet the needs of robotic welding. This method is expected to improve the level of robotic autonomous welding operation based on 3D visual sensing for workpieces with uncertain geometric and positional information.

  • [1]
    Lei T, Rong Y, Wang H, et al. A review of vision-aided robotic welding[J]. Computers in Industry, 2020, 123: 103326. doi: 10.1016/j.compind.2020.103326
    [2]
    Wu P, Gan Y, Dai X. The weld extraction algorithm for robotic arc welding based on 3D laser sensor [C]//Chinese Control And Decision Conference (CCDC), 2019: 998 − 1002.
    [3]
    Zhao Z, Luo J, Wang Y, et al. Additive seam tracking technology based on laser vision[J]. The International Journal of Advanced Manufacturing Technology, 2021, 116(1-2): 197 − 211. doi: 10.1007/s00170-021-07380-0
    [4]
    Zou Y, Chen J, Wei X. Research on a real-time pose estimation method for a seam tracking system[J]. Optics and Lasers in Engineering, 2020, 127: 105947.1 − 105947.15.
    [5]
    Yu S, Guan Y, Yang Z, et al. Multiseam tracking with a portable robotic welding system in unstructured environments[J]. The International Journal of Advanced Manufacturing Technology, 2022, 122(3): 2077 − 2094.
    [6]
    Li J, Jing F, Li E. Rgb-d sensor-based auto path generation method for arc welding robot [C]//Chinese Control and Decision Conference (CCDC), 2016: 4390 − 4395.
    [7]
    Yang L, Liu Y, Peng J, et al. A novel system for off-line 3D seam extraction and path planning based on point cloud segmentation for arc welding robot[J]. Robotics and Computer-Integrated Manufacturing, 2020, 64(3): 101929.
    [8]
    Geng, Y, Lai, M, Tian, X, et al. A novel seam extraction and path planning method for robotic welding of medium-thickness plate structural parts based on 3D vision[J]. Robotics and Computer-Integrated Manufacturing, 2023, 79: 102433. doi: 10.1016/j.rcim.2022.102433
    [9]
    Zhou P, Peng R, Xu M, et al. Path planning with automatic seam extraction over point cloud models for robotic arc welding[J]. IEEE Robotics and Automation Letters, 2021, 6(3): 5002 − 5009. doi: 10.1109/LRA.2021.3070828
    [10]
    陈志翔, 卢振洋, 殷树言, 等. 焊缝位姿及焊枪位姿的模型[J]. 机械工程学报, 2003, 39(7): 59 − 62. doi: 10.3321/j.issn:0577-6686.2003.07.013

    Chen Zhixiang, Lu Zhenyang, Yin Shuyan, et al. Models of weld pose and welding torch pose[J]. Journal of Mechanical Engineering, 2003, 39(7): 59 − 62. doi: 10.3321/j.issn:0577-6686.2003.07.013
    [11]
    张天一, 朱志明, 朱传辉. 基于视觉与重力融合传感的焊枪位姿反馈控制[J]. 焊接学报, 2021, 42(11): 1 − 7. doi: 10.12073/j.hjxb.20210412001

    Zhang Tianyi, Zhu Zhiming, Zhu Chuanhui. Position and pose feedback control of welding torch based on the fusion of vision and gravity sensing[J]. Transactions of the China Welding Institution, 2021, 42(11): 1 − 7. doi: 10.12073/j.hjxb.20210412001
    [12]
    Zhou B, Liu Y, Xiao Y, et al. Intelligent guidance programming of welding robot for 3D curved welding seam[J]. IEEE Access, 2021, 9: 42345 − 42357. doi: 10.1109/ACCESS.2021.3065956
    [13]
    Kim J, Lee J, Chung M, et al. Multiple weld seam extraction from RGB-depth images for automatic robotic welding via point cloud registration[J]. Multimedia Tools and Applications, 2021, 80(6): 9703 − 9719. doi: 10.1007/s11042-020-10138-7
    [14]
    Lu X, Liu Y, Li K. Fast 3D line segment detection from unorganized point cloud [EB/OL]. [2019-01-23]. https://arxiv.org/abs/1901.02532.
    [15]
    Tran C, Lin C. An intelligent path planning of welding robot based on multi-sensor interaction[J]. IEEE Sensors Journal, 2023, 23(8): 8591 − 8604. doi: 10.1109/JSEN.2023.3252637
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