无需示教即可校准激光视觉传感器时空偏差，提升焊接机器人精度。

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.