  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.
