TY - JOUR
T1 - A new hand-eye calibration approach for fracture reduction robot
AU - Wang, Lifeng
AU - Wang, Tianmiao
AU - Tang, Peifu
AU - Hu, Lei
AU - Liu, Wenyong
AU - Han, Zhonghao
AU - Hao, Ming
AU - Liu, Hongpeng
AU - Wang, Kun
AU - Zhao, Yanpeng
AU - Guo, Na
AU - Cao, Yanxiang
AU - Li, Changsheng
N1 - Publisher Copyright:
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2017/10/31
Y1 - 2017/10/31
N2 - Objective: The hand-eye calibration is used to determine the transformation between the end-effector and the camera marker of the robot. But the robot movement in traditional method would be time-consuming, inaccurate and even unavailable in some conditions. The method presented in this article can complete the calibration without any movement and is more suitable in clinical applications. Methods: Instead of solving the classic non-linear equation AX = XB, we collected the points on X and Y axes of the tool coordinate system (TCS) with the visual probe and fitted them using the singular value decomposition algorithm (SVD). Then, the transformation was obtained with the data of the tool center point (TCP). A comparison test was conducted to verify the performance of the method. Results: The average translation error and orientation error of the new method are 0.12 ± 0.122 mm and 0.18 ± 0.112° respectively, while they are 0.357 ± 0.347 mm and 0.416 ± 0.234° correspondingly in the traditional method. Conclusions: The high accuracy of the method indicates that it is a good candidate for medical robots, which usually need to work in a sterile environment.
AB - Objective: The hand-eye calibration is used to determine the transformation between the end-effector and the camera marker of the robot. But the robot movement in traditional method would be time-consuming, inaccurate and even unavailable in some conditions. The method presented in this article can complete the calibration without any movement and is more suitable in clinical applications. Methods: Instead of solving the classic non-linear equation AX = XB, we collected the points on X and Y axes of the tool coordinate system (TCS) with the visual probe and fitted them using the singular value decomposition algorithm (SVD). Then, the transformation was obtained with the data of the tool center point (TCP). A comparison test was conducted to verify the performance of the method. Results: The average translation error and orientation error of the new method are 0.12 ± 0.122 mm and 0.18 ± 0.112° respectively, while they are 0.357 ± 0.347 mm and 0.416 ± 0.234° correspondingly in the traditional method. Conclusions: The high accuracy of the method indicates that it is a good candidate for medical robots, which usually need to work in a sterile environment.
KW - Hand-Eye Calibration
KW - fracture reduction robot
KW - singular value decomposition
UR - http://www.scopus.com/inward/record.url?scp=85029908694&partnerID=8YFLogxK
U2 - 10.1080/24699322.2017.1379254
DO - 10.1080/24699322.2017.1379254
M3 - Article
C2 - 28938847
AN - SCOPUS:85029908694
SN - 1092-9088
VL - 22
SP - 113
EP - 119
JO - Computer Assisted Surgery
JF - Computer Assisted Surgery
ER -