Zhang Lilong, Cao Tong, Liu Da
School of Mechanical Engineering, USTB, Beijing 100083, P.R.China.
Robotics Institute, Beihang University, Beijing 100191,
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2017 Apr 25;34(2):271-277. doi: 10.7507/1001-5515.201607037.
A new one-time registration method was developed in this research for hand-eye calibration of a surgical robot to simplify the operation process and reduce the preparation time. And a new and practical method is introduced in this research to optimize the end-tool parameters of the surgical robot based on analysis of the error sources in this registration method. In the process with one-time registration method, firstly a marker on the end-tool of the robot was recognized by a fixed binocular camera, and then the orientation and position of the marker were calculated based on the joint parameters of the robot. Secondly the relationship between the camera coordinate system and the robot base coordinate system could be established to complete the hand-eye calibration. Because of manufacturing and assembly errors of robot end-tool, an error equation was established with the transformation matrix between the robot end coordinate system and the robot end-tool coordinate system as the variable. Numerical optimization was employed to optimize end-tool parameters of the robot. The experimental results showed that the one-time registration method could significantly improve the efficiency of the robot hand-eye calibration compared with the existing methods. The parameter optimization method could significantly improve the absolute positioning accuracy of the one-time registration method. The absolute positioning accuracy of the one-time registration method can meet the requirements of the clinical surgery.
本研究开发了一种新的一次性注册方法用于手术机器人的手眼校准,以简化操作过程并减少准备时间。并且本研究引入了一种新的实用方法,基于对该注册方法中误差源的分析来优化手术机器人的末端工具参数。在使用一次性注册方法的过程中,首先由固定的双目相机识别机器人末端工具上的一个标记,然后基于机器人的关节参数计算该标记的方位和位置。其次,可以建立相机坐标系与机器人基座坐标系之间的关系以完成手眼校准。由于机器人末端工具的制造和装配误差,以机器人末端坐标系与机器人末端工具坐标系之间的变换矩阵为变量建立了误差方程。采用数值优化方法来优化机器人的末端工具参数。实验结果表明,与现有方法相比,一次性注册方法可显著提高机器人手眼校准的效率。参数优化方法可显著提高一次性注册方法的绝对定位精度。一次性注册方法的绝对定位精度能够满足临床手术的要求。