On Flange-based 3D Hand-Eye Calibration for Soft Robotic Tactile Welding
<|reference_start|>On Flange-based 3D Hand-Eye Calibration for Soft Robotic Tactile Welding: This paper investigates the direct application of standardized designs on the robot for conducting robot hand-eye calibration by employing 3D scanners with collaborative robots. The well-established geometric features of the robot flange are exploited by directly capturing its point cloud data. In particular, an iterative method is proposed to facilitate point cloud processing toward a refined calibration outcome. Several extensive experiments are conducted over a range of collaborative robots, including Universal Robots UR5 & UR10 e-series, Franka Emika, and AUBO i5 using an industrial-grade 3D scanner Photoneo Phoxi S & M and a commercial-grade 3D scanner Microsoft Azure Kinect DK. Experimental results show that translational and rotational errors converge efficiently to less than 0.28 mm and 0.25 degrees, respectively, achieving a hand-eye calibration accuracy as high as the camera's resolution, probing the hardware limit. A welding seam tracking system is presented, combining the flange-based calibration method with soft tactile sensing. The experiment results show that the system enables the robot to adjust its motion in real-time, ensuring consistent weld quality and paving the way for more efficient and adaptable manufacturing processes.<|reference_end|>
@article{han2024on,
    title={On Flange-based 3D Hand-Eye Calibration for Soft Robotic Tactile Welding},
    author={Xudong Han and Ning Guo and Yu Jie and He Wang and Fang Wan and
  Chaoyang Song},
    journal={arXiv preprint arXiv:2407.16041},
    year={2024},
    doi={10.1016/j.measurement.2024.115376},
    archivePrefix={arXiv},
    eprint={2407.16041},
    primaryClass={cs.RO}
}