Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-22T06:47:44.482Z Has data issue: false hasContentIssue false
  • English
  • Français

A new kinematics method based on a dynamic visual window for a surgical robot

Published online by Cambridge University Press:  04 September 2013

Lingtao Yu ,
Zhengyu Wang ,
Peng Yu ,
Tao Wang ,
Huajian Song  and
Zhijiang Du
Lingtao Yu
Affiliation:
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, P. R. China State Key Laboratory of Robotics and System (HIT), Harbin Institute of Technology, Harbin 150080, P. R. China
Zhengyu Wang*
Affiliation:
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, P. R. China
Peng Yu
Affiliation:
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, P. R. China
Tao Wang
Affiliation:
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, P. R. China
Huajian Song
Affiliation:
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, P. R. China
Zhijiang Du
Affiliation:
State Key Laboratory of Robotics and System (HIT), Harbin Institute of Technology, Harbin 150080, P. R. China
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

This paper proposes a new effective kinematics method based on the dynamic visual window (DVW) for a surgical robot that is equipped with two instrument arms and one laparoscope arm, to enable doctors to achieve operations with their visual habits under the laparoscopic visual environment. The problem of the consistency principle between the doctor's operations under the visual window's feedback and the master–slave operations of the surgical robot is solved. The kinematics models of the surgical robotic arms are established, and the new kinematics methods based on the DVW of the laparoscope and instrument arms are proposed according to their inverse kinematics with respect to the visual coordinate system. Finally, the proposed kinematics method is verified by simulation experiments based on the theoretical algorithm and the mechanism model; the multiple sets of the simulation data are presented to illustrate the correctness and feasibility of the new method in this research.

Keywords

RoboticsSurgical robotKinematicsDynamic visual windowSimulations
Type
Articles
Information
Robotica , Volume 32 , Issue 4 , July 2014 , pp. 571 - 589
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Sunga, G. T. and Gill, I. S., “Robotic laparoscopic surgery: A comparison of the da Vinci and Zeus systems,” Urology 58 (6), 893–898 (2001).CrossRefGoogle Scholar
2.Valero, R., Ko, Y. H., Chauhan, S., Schatloff, O., Sivaraman, A., Coelho, R. F., Ortega, F., Palmer, K. J., Sanchez-Salas, R., Davila, H., Cathelineau, X. and Patel, V. R., “Robotic surgery: History and teaching impact,” Actas Urol. Esp. 35 (9), 540–545 (2011).Google Scholar
3.Haidegger, T. and Benyo, Z., “Surgical robotic support for long duration space missions,” Acta Astronaut. 63 (7–10), 996–1005 (2008).Google Scholar
4.Monsarrat, N., Collinet, P., Narducci, F., Leblanc, E. and Vinatier, D., “Robotic assistance in gynaecological surgery: State-of-the-art,” Gynécol. Obstét. Fertil. 37 (5), 415–424 (2009).Google Scholar
5.Giuseppe, T., Ilaria, P., Francesca, P. and Alfred, C., “Economic evaluation of da Vinci-assisted robotic surgery: A systematic review,” Surg. Endosc. 26 (3), 598–606 (2012).Google Scholar
6.Hagn, U., Nickl, M., Jörg, S., Passig, G., Bahls, T., Nothhelfer, A., Hacker, F., Le-Tien, L., Albu-Schäffer, A., Konietschke, R., Grebenstein, M., Warpup, R., Haslinger, R., Frommberger, M. and Hirzinger, G., “The DLR MIRO: a versatile lightweight robot for surgical applications,” Ind. Robot: Int. J. 35 (4), 324–336 (2008).Google Scholar
7.Konietschke, R., Hagn, U., Nickl, M., Jörg, S., Tobergte, A., Passig, G., Seibold, U., Le-Tien, L., Kübler, B., Gröger, M., Fröhlich, F., Rink, C., Albu-Schäffer, A., Grebenstein, M., Ortmaier, T. and Hirzinger, G., “The DLR MiroSurge: A Robotic System for Surgery,” In: 2009 IEEE International Conference on Robotics and Automation, Kobe, Japan (May 12–17, 2009) pp. 1589–1590.CrossRefGoogle Scholar
8.Lum, M. J. H., Friedman, D. C. W., Sankaranarayanan, G., King, H., Fodero, K., Hannaford, B., J. Rosen and Sinanan, M. N., “The RAVEN: Design and validation of a telesurgery system,” Int. J. Robot. Res. 28 (9), 1183–1197 (2009).Google Scholar
9.Jacob, R., Mitchell, L., Mika, S. and Blake, H., “Raven: Developing a Surgical Robot from a Concept to a Transatlantic Teleoperation Experiment,” In: Surgical Robotics: Systems Applications and Visions (Rosen, J., B. Hannaford and Satava, R. M., eds.), (Springer, New York, US, 2011) pp. 159–197.Google Scholar
10.Hornyak, T., 2010. Paging Raven II: the open-source surgery robot. CNET [internet]. Available at: http://news.cnet.com/8301-17938_105-573624501/paging-raven-ii-the-open-source-surgery-robot/.Google Scholar
11.van den Bedema, L., Rosiellea, N. and Steinbuch, M., “Design of Slave Robot for Laparoscopic and Thoracoscopic Surgery,” 20th International Conference of Society for Medical Innovation and Technology, Vienna, Austria (August 28–30, 2008).Google Scholar
12.Berkelman, P. and Ma, J., “A compact modular teleoperated robotic system for laparoscopic surgery,” Int. J. Robot. Res. 28 (9), 1198–1215 (2009).CrossRefGoogle ScholarPubMed
13.Weede, O., Mönnich, H., Müller, B. and Wörn, H., “An Intelligent and Autonomous Endoscopic Guidance System for Minimally Invasive Surgery,” 2011 IEEE International Conference on Robotics and Automation, Shanghai, China (May 9–13, 2011) pp. 5762–5768.Google Scholar
14.Staub, C., Lenz, C., Panin, G., Knoll, A. and Bauernschmitt, R., “Contour-Based Surgical Instrument Tracking Supported by Kinematic Prediction,” Proceedings of the 2010 3rd IEEE RAS and EMBS, Tokyo, Japan (September 26–29, 2010) pp. 746–752.Google Scholar
15.Tully, S., Kantor, G., Zenati, M. A. and Choset, H., “Shape Estimation for Image-Guided Surgery with a Highly Articulated Snake Robot,” 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, USA (September 25–30, 2011) pp. 1353–1358.Google Scholar
16.Gherman, B., Pislan, D., Vaida, C. and Plitea, N., “Development of inverse dynamic model for a surgical hybrid parallel robot with equivalent lumped masses,” Robot. Comput.-Integr. Manuf. 28 (3), 402–415 (2012).Google Scholar
17.Brouwer, O. R., Buckle, T., Bunschoten, A., Kuil, J., Vahrmeijer, A. L., Wendler, T., Valdés-Olmos, R. A., van der Poel, H. G. and Leeuwen, F. W. B. van, “Image navigation as a means to expand the boundaries of fluorescence-guided surgery,” Phys. Med. Biol. 57 (10), 3123–3136 (2012).Google Scholar