Literature DB >> 33746640

Camera-Robot Calibration for the da Vinci® Robotic Surgery System.

Orhan Özgüner1, Thomas Shkurti1, Siqi Huang1, Ran Hao1, Russell C Jackson1, Wyatt S Newman1, M Cenk Çavuşoğlu1.   

Abstract

The development of autonomous or semi-autonomous surgical robots stands to improve the performance of existing teleoperated equipment, but requires fine hand-eye calibration between the free-moving endoscopic camera and patient-side manipulator arms (PSMs). A novel method of solving this problem for the da Vinci® robotic surgical system and kinematically similar systems is presented. First, a series of image-processing and optical-tracking operations are performed to compute the coordinate transformation between the endoscopic camera view frame and an optical-tracking marker permanently affixed to the camera body. Then, the kinematic properties of the PSM are exploited to compute the coordinate transformation between the kinematic base frame of the PSM and an optical marker permanently affixed thereto. Using these transformations, it is then possible to compute the spatial relationship between the PSM and the endoscopic camera using only one tracker snapshot of the two markers. The effectiveness of this calibration is demonstrated by successfully guiding the PSM end effector to points of interest identified through the camera. Additional tests on a surgical task, namely grasping a surgical needle, are also performed to validate the proposed method. The resulting visually-guided robot positioning accuracy is better than the earlier hand-eye calibration results reported in the literature for the da Vinci® system, while supporting intraoperative update of the calibration and requiring only devices that are already commonly used in the surgical environment.

Entities:  

Keywords:  Medical Robots and Systems; Surgical Robotics: Laparoscopy; da Vinci Research Kit (dVRK)

Year:  2020        PMID: 33746640      PMCID: PMC7978174          DOI: 10.1109/tase.2020.2986503

Source DB:  PubMed          Journal:  IEEE Trans Autom Sci Eng        ISSN: 1545-5955            Impact factor:   5.083


  10 in total

1.  Comparative tracking error analysis of five different optical tracking systems.

Authors:  R Khadem; C C Yeh; M Sadeghi-Tehrani; M R Bax; J A Johnson; J N Welch; E P Wilkinson; R Shahidi
Journal:  Comput Aided Surg       Date:  2000

2.  Comparison of robotic versus laparoscopic skills: is there a difference in the learning curve?

Authors:  Paulos Yohannes; Paul Rotariu; Peter Pinto; Arthur D Smith; Benjamin R Lee
Journal:  Urology       Date:  2002-07       Impact factor: 2.649

3.  Needle Path Planning for Autonomous Robotic Surgical Suturing.

Authors:  Russell C Jackson; M Cenk Cavuşoğlu
Journal:  IEEE Int Conf Robot Autom       Date:  2013-12-31

Review 4.  Evolution of autonomous and semi-autonomous robotic surgical systems: a review of the literature.

Authors:  G P Moustris; S C Hiridis; K M Deliparaschos; K M Konstantinidis
Journal:  Int J Med Robot       Date:  2011-08-03       Impact factor: 2.547

5.  Vision-Based Surgical Tool Pose Estimation for the da Vinci® Robotic Surgical System.

Authors:  Ran Hao; Orhan Özgüner; M Cenk Çavuşoğlu
Journal:  Rep U S       Date:  2019-01-07

6.  Raven-II: an open platform for surgical robotics research.

Authors:  Blake Hannaford; Jacob Rosen; Diana W Friedman; Hawkeye King; Phillip Roan; Lei Cheng; Daniel Glozman; Ji Ma; Sina Nia Kosari; Lee White
Journal:  IEEE Trans Biomed Eng       Date:  2012-11-29       Impact factor: 4.538

7.  Needle Grasp and Entry Port Selection for Automatic Execution of Suturing Tasks in Robotic Minimally Invasive Surgery.

Authors:  Taoming Liu; M Cenk Çavuşoğlu
Journal:  IEEE Trans Autom Sci Eng       Date:  2016-04-05       Impact factor: 5.083

8.  Needle-Tissue Interaction Force State Estimation for Robotic Surgical Suturing.

Authors:  Russell C Jackson; Viraj Desai; Jean P Castillo; M Cenk Çavuşoğlu
Journal:  Rep U S       Date:  2016-10

9.  On-demand calibration and evaluation for electromagnetically tracked laparoscope in augmented reality visualization.

Authors:  Xinyang Liu; William Plishker; George Zaki; Sukryool Kang; Timothy D Kane; Raj Shekhar
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-06-01       Impact factor: 2.924

10.  A computationally efficient method for hand-eye calibration.

Authors:  Zhiqiang Zhang; Lin Zhang; Guang-Zhong Yang
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-07-19       Impact factor: 2.924

  10 in total

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