A computationally efficient method for hand-eye calibration

被引:44
作者
Zhang, Zhiqiang [1 ]
Zhang, Lin [2 ]
Yang, Guang-Zhong [2 ]
机构
[1] Univ Leeds, Sch Elect & Elect Engn, Leeds, W Yorkshire, England
[2] Imperial Coll London, Hamylyn Ctr, London, England
基金
英国工程与自然科学研究理事会;
关键词
Minimally invasive surgery; Robot-camera calibration; Hand-eye calibration; Optimization; 3D TRACKING; ALGORITHM; SURGERY; TISSUE; OPTIMIZATION; QUATERNIONS; SENSOR;
D O I
10.1007/s11548-017-1646-x
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Surgical robots with cooperative control and semiautonomous features have shown increasing clinical potential, particularly for repetitive tasks under imaging and vision guidance. Effective performance of an autonomous task requires accurate hand-eye calibration so that the transformation between the robot coordinate frame and the camera coordinates is well defined. In practice, due to changes in surgical instruments, online hand-eye calibration must be performed regularly. In order to ensure seamless execution of the surgical procedure without affecting the normal surgical workflow, it is important to derive fast and efficient hand-eye calibration methods. We present a computationally efficient iterative method for hand-eye calibration. In this method, dual quaternion is introduced to represent the rigid transformation, and a two-step iterative method is proposed to recover the real and dual parts of the dual quaternion simultaneously, and thus the estimation of rotation and translation of the transformation. The proposed method was applied to determine the rigid transformation between the stereo laparoscope and the robot manipulator. Promising experimental and simulation results have shown significant convergence speed improvement to 3 iterations from larger than 30 with regard to standard optimization method, which illustrates the effectiveness and efficiency of the proposed method.
引用
收藏
页码:1775 / 1787
页数:13
相关论文
共 40 条
[1]  
Ackerman MK, 2014, IEEE INT CONF ROBOT, P4900, DOI 10.1109/ICRA.2014.6907577
[2]   3-D Ultrasound-Guided Robotic Needle Steering in Biological Tissue [J].
Adebar, Troy K. ;
Fletcher, Ashley E. ;
Okamura, Allison M. .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2014, 61 (12) :2899-2910
[3]  
Andreff N., 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062), P430, DOI 10.1109/IM.1999.805374
[4]   The da Vinci telerobotic surgical system: the virtual operative field and telepresence surgery [J].
Ballantyne, GH ;
Moll, F .
SURGICAL CLINICS OF NORTH AMERICA, 2003, 83 (06) :1293-+
[5]   From Passive Tool Holders to Microsurgeons: Safer, Smaller, Smarter Surgical Robots [J].
Bergeles, Christos ;
Yang, Guang-Zhong .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2014, 61 (05) :1565-1576
[6]  
Chen Zihan, 2013, P MICCAI WORKSH, P22
[7]   FINDING THE POSITION AND ORIENTATION OF A SENSOR ON A ROBOT MANIPULATOR USING QUATERNIONS [J].
CHOU, JCK ;
KAMEL, M .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 1991, 10 (03) :240-254
[8]   Hand-eye calibration using dual quaternions [J].
Daniilidis, K .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 1999, 18 (03) :286-298
[9]   Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery [J].
Du, Xiaofei ;
Allan, Maximilian ;
Dore, Alessio ;
Ourselin, Sebastien ;
Hawkes, David ;
Kelly, John D. ;
Stoyanov, Danail .
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2016, 11 (06) :1109-1119
[10]   Soft Boundary Approach for Unsupervised Gesture Segmentation in Robotic-Assisted Surgery [J].
Fard, Mahtab Jahanbani ;
Ameri, Sattar ;
Chinnam, Ratna Babu ;
Ellis, R. Darin .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2017, 2 (01) :171-178