Lin Jinsong, Feng Yuxing, Ren Wenze, Feng Jiahui, Zheng Jun
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
Sensors (Basel). 2024 Nov 26;24(23):7554. doi: 10.3390/s24237554.
The hand-eye calibration of laser profilers and industrial robots is a critical component of the laser vision system in welding applications. To improve calibration accuracy and efficiency, this study proposes a position-constrained calibration compensation algorithm aimed at optimizing the hand-eye transformation matrix. Initially, the laser profiler is mounted on the robot and used to scan a standard sphere from various poses to obtain the theoretical center coordinates of the sphere, which are then utilized to compute the hand-eye transformation matrix. Subsequently, the positional data of the standard sphere's surface are collected at different poses using the welding gun tip mounted on the robot, allowing for the fitting of the sphere's center coordinates as calibration values. Finally, by minimizing the error between the theoretical and calibrated sphere center coordinates, the optimal hand-eye transformation matrix is derived. Experimental results demonstrate that, following error compensation, the average distance error in hand-eye calibration decreased from 4.5731 mm to 0.7069 mm, indicating that the proposed calibration method is both reliable and effective.
激光轮廓仪与工业机器人的手眼校准是焊接应用中激光视觉系统的关键组成部分。为提高校准精度和效率,本研究提出一种位置约束校准补偿算法,旨在优化手眼变换矩阵。首先,将激光轮廓仪安装在机器人上,从不同姿态扫描标准球体以获取球体的理论中心坐标,然后利用这些坐标计算手眼变换矩阵。随后,使用安装在机器人上的焊枪尖端在不同姿态收集标准球体表面的位置数据,从而拟合出球体的中心坐标作为校准值。最后,通过最小化理论球体中心坐标与校准后球体中心坐标之间的误差,得出最优手眼变换矩阵。实验结果表明,经过误差补偿后,手眼校准中的平均距离误差从4.5731毫米降至0.7069毫米,这表明所提出校准方法可靠且有效。