为了避免机器人模型误差对三维形貌柔性测量系统手眼标定的影响,对手眼关系的标定方法进行了研究。提出了一种融合特征点拟合的手眼标定方法。将三维形貌扫描仪安装在工业机器人末端搭建三维形貌柔性测量系统。标定时,首先利用激光跟踪仪对工业机器人末端法兰盘坐标系进行测量,得到两者转换关系；然后,利用三维形貌扫描仪和激光跟踪仪对空间固定的特征点组进行测量,利用特征点约束和基于罗德里格矩阵的算法求解两者转换关系即可间接地求解出手眼关系。基于ATOS三维扫描仪、安川HP20D机器人和API公司生产的激光跟踪仪进行了手眼标定实验,并进行了精度验证。结果表明：标定后的三维形貌柔性测量系统,其重复性测量精度(3σ)不超过0.1 mm,长度测量精度的均方根误差在0.2 mm以内,点云拼接精度优于±0.7 mm。该方法有效避免了传统手眼标定过程中会引入机器人模型误差的问题,在求解手眼关系解时采用了线性的解法,并且适用于三维形貌柔性测量系统。

In order to avoid the influence of robot model error on the hand-eye calibration of a three-dimensional shape flexible measurement system,the hand-eye calibration method was investigated . A calibration method based on the feature points fitting was proposed. The 3D shape measurement robotic system was established with a 3D shape scanner mounted on the robot end. In the calibration, the robot end coordinate system was measured with a laser tracker to obtain their transformation relationship. Then,3D shape scanner and laser tracker were used for measuring feature points which fixed in the measurement field, and the transformation relationship between them could be identified by the constraint of feature points and the algorithm of Rodrigues matrix. Consequently, the hand-eye relationship was established directly. Experiment of hand-eye calibration was based on ATOS 3D optical scanner, Yaskawa-Hp20D robot and API laser tracer, and accuracy verification experiments were carried out. The verification experimental results show that the repeatability accuracy (3σ) of 3D shape robotic measurement system is better than 0.1 mm , the root-mean-square (RMS) error of distance is within 0.2 mm, and the accuracy of point cloud stitching is better than 0.7 mm after calibration. Meanwhile, this method can effectively avoid robotic model error which can be introduced in the process of traditional hand-eye calibration, the solution procedure adopts the linear method, and this method adapts to the 3D shape measurement robotic system.