Laser vision sensors (LVS) are critical perception modules for industrial robots, facilitating real-time acquisition of workpiece geometric data in welding applications. However, the camera communication delay will lead to a temporal desynchronization between captured images and the robot motions. Additionally, hand-eye extrinsic parameters may vary during prolonged measurement. To address these issues, we introduce a measurement model of LVS considering the effect of the camera's time-offset and propose a teaching-free spatiotemporal calibration method utilizing line constraints. This method involves a robot equipped with an LVS repeatedly scanning straight-line fillet welds using S-shaped trajectories. Regardless of the robot's orientation changes, all measured welding positions are constrained to a straight-line, represented by Plucker coordinates. Moreover, a nonlinear optimization model based on straight-line constraints is established. Subsequently, the Levenberg-Marquardt algorithm (LMA) is employed to optimize parameters, including time-offset, hand-eye extrinsic parameters, and straight-line parameters. The feasibility and accuracy of the proposed approach are quantitatively validated through experiments on curved weld scanning. We open-sourced the code, dataset, and simulation report at https://anonymous.4open.science/r/LVS_ST_CALIB-015F/README.md.

翻译：激光视觉传感器是工业机器人的关键感知模块，在焊接应用中可实现工件几何数据的实时采集。然而，相机通信延迟会导致采集图像与机器人运动之间的时间不同步。此外，手眼外参在长时间测量过程中可能发生变化。为解决这些问题，我们提出了一个考虑相机时间偏移影响的激光视觉传感器测量模型，并利用直线约束提出了一种免示教的时空标定方法。该方法通过配备激光视觉传感器的机器人沿S形轨迹重复扫描直线角焊缝。无论机器人姿态如何变化，所有测量的焊接位置均被约束在一条直线上，该直线由普吕克坐标表示。进一步地，我们建立了一个基于直线约束的非线性优化模型，随后采用Levenberg-Marquardt算法对时间偏移、手眼外参及直线参数进行优化。通过在曲线焊缝扫描实验中的定量验证，证明了所提方法的可行性与准确性。相关代码、数据集及仿真报告已开源，地址为：https://anonymous.4open.science/r/LVS_ST_CALIB-015F/README.md。