Optimization of end-tool parameters based on robot hand-eye calibration_Journal of Biomedical Engineering

Authors：

ZHANG Lilong ¹ , CAO Tong ¹ ,  LIU Da ²

1. School of Mechanical Engineering, USTB, Beijing 100083, P.R.China;
2. Robotics Institute, Beihang University, Beijing 100191, P.R.China;

Corresponding author：

LIU Da, Email: drliuda@aliyun.com

Keywords：

surgical robot; one-time registration; hand-eye calibration; parameter optimization

DOI：

10.7507/1001-5515.201607037

Video：

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Abstract Full text Figures/Tables Video References Cited by

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.

Citation： ZHANG Lilong, CAO Tong, LIU Da. Optimization of end-tool parameters based on robot hand-eye calibration. Journal of Biomedical Engineering, 2017, 34(2): 271-277. doi: 10.7507/1001-5515.201607037 Copy

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14.	曹彤, 许倩, 和丽, 等. 微创外科机器人导航系统空间映射精度分析与仿真. 图学学报, 2012, 33(4): 103-109.
15.	胡小平, 左富勇, 谢珂. 微装配机器人手眼标定方法研究. 仪器仪表学报, 2012, 33(7): 1521-1526.
16.	胡小平, 谢珂, 彭涛. 一种新的双目固定式机器人三维视觉定位方法. 光电工程, 2014, 41(8): 10-15.
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1. Wang T, Wei J, Liu D, et al. An internet robot assistant tele-neurosurgery system case// 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing, 2006: 2845-2849.
2. 翟伟明, 赵雁南, 王家廞, 等. 机器人辅助无框架定位脑外科手术系统. 高技术通讯, 2005, 15(4): 33-36.
3. 陈梦东, 王田苗, 刘达, 等. 机器人辅助微损伤神经外科手术系统的研究及其临床应用.中国生物医学工程学报, 2000, 19(2): 145-151.
4. 许海霞, 王耀南, 万琴, 等. 一种机器人手眼关系自标定方法. 机器人, 2008, 30(4): 373-378.
5. 刘军传, 张玉茹, 李振. 神经外科机器人定位精度研究. 机器人, 2007, 29(2): 123-127.
6. Morgan P S, Carter T, Davis S, et al. The application accuracy of the Pathfinder neurosurgical robot. International Congress, 2003, 1256(3): 561-567.
7. 王君臣, 王田苗, 杨艳, 等. 非线性最优机器人手眼标定. 西安交通大学学报, 2011, 45(9): 15-20, 89.
8. 沈爱华, 罗印升, 宋伟. 一种基于双目视觉的手眼标定方法. 机械设计与制造工程, 2016, 45(5): 42-46.
9. 张召瑞, 张旭, 郑泽龙, 等. 融合旋转平移信息的机器人手眼标定方法.仪器仪表学报, 2015, 36(11): 2443-2450.
10. 洪磊, 嵇保健, 王玉国, 等. 改进的单特征点机器人手眼自标定方法. 北京邮电大学学报, 2016, 39(1): 96-101.
11. Muis A, Ohnishi K. Eye-to-hand approach on eye-in-hand configuration within real-time visual servoing. IEEE-ASME Transactions on Mechatronics, 2005, 10(4): 404-410.
12. Wei Z Z, Zhang B, Zhang G J. Rapid hand-eye calibration of dual robot system. Optics & Precision Engineering, 2011, 44(5): 359-367.
13. Malti A, Barreto J P. Robust hand-eye calibration for computer aided medical endoscopy// 2010 7th International Conference on Robotics & Automation. Fuchal: 2010: 5543-5549.
14. 曹彤, 许倩, 和丽, 等. 微创外科机器人导航系统空间映射精度分析与仿真. 图学学报, 2012, 33(4): 103-109.
15. 胡小平, 左富勇, 谢珂. 微装配机器人手眼标定方法研究. 仪器仪表学报, 2012, 33(7): 1521-1526.
16. 胡小平, 谢珂, 彭涛. 一种新的双目固定式机器人三维视觉定位方法. 光电工程, 2014, 41(8): 10-15.
17. Craig J J. 机器人学导论. 第3版. 北京: 机械工业出版社, 2006: 19-77.
18. 王荣军, 刘达, 贾培发. 医用机器人运动学参数最优化设计. 机器人, 2007, 29(4): 368-373.

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