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（LVS）是工业机器人的关键感知模块，在焊接应用中能够实时获取工件几何数据。然而，相机通信延迟会导致采集图像与机器人运动之间存在时间不同步问题。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，我们提出了一种考虑相机时间偏移影响的LVS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。该方法通过搭载LVS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，所有测量的焊缝位置均被约束在一条直线上，该直线采用普吕克坐标表示。此外，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（LMA）对参数进行优化，包括时间偏移、手眼外参以及直线参数。通过在曲线焊缝扫描上的实验，定量验证了所提方法的可行性与精度。我们在 https://anonymous.4open.science/r/LVS_ST_CALIB-015F/README.md 开源了代码、数据集及仿真报告。