Hostname: page-component-7dd5485656-tbj44 Total loading time: 0 Render date: 2025-10-30T23:09:40.361Z Has data issue: false hasContentIssue false
  • English
  • Français

Robotic surgery: from autonomous systems to intelligent tools

Published online by Cambridge University Press:  27 August 2009

Ferdinando Rodriguez y Baena  and
Brian Davies
Ferdinando Rodriguez y Baena*
Affiliation:
The Mechatronics in Medicine Laboratory, Department of Mechanical Engineering, Imperial College, Exhibition Road, London, SW7 2AZ, UK
Brian Davies
Affiliation:
The Italian Institute of Technology (Fondazione Istituto Italiano di Tecnologia), Via Morego 16163 Genoa, Italy
*
*Corresponding author. E-mail: f.rodriguez@imperial.ac.uk
Get access Rights & Permissions [Opens in a new window]

Summary

A brief history of robotic surgery is provided, which describes the transition from autonomous robots to hands-on systems that are under the direct control of the surgeon. An example of the latter is the Acrobot (for active-constraint robot) system used in orthopaedics, whilst soft-tissue surgery is illustrated by the daVinci telemanipulator system. Non-technological aspects of robotic surgery have often been a major impediment to their widespread clinical use. These are discussed in detail, together with the role of navigation systems, which are considered a major competitor to surgical robots. A detailed description is then given of a registration method for robots to achieve improved accuracy. Registration is a major source of error in robotic surgery, particularly in orthopaedics. The paper describes the design and clinical implementation of a novel method, coined the bounded registration method, applied to minimally invasive registration of the femur. Results of simulations which compare the performance of bounded registration with a standard implementation of the iterative closest point algorithm are also presented, alongside a description of their application in the Acrobot hands-on robot, used clinically for uni-condylar knee arthroplasty.

Keywords

Computer-assisted surgeryRobotic surgerySurgical navigationIntelligent toolsSmart toolsRegistrationBounded registration methodIterative closest point

Information

Type
Article
Information
Robotica , Volume 28 , Special Issue 2: Surgical Robotics: System Development, Application Study and Performance Analysis , March 2010 , pp. 163 - 170
Copyright
Copyright © Cambridge University Press 2009

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.)

Article purchase

Temporarily unavailable

References

1. Kwoh, Y., Hou, J., Jonckheere, E. and Hayati, S., “A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery,” IEEE Trans. Biomed. Eng. 35 (2), 153–160 (1988).CrossRefGoogle ScholarPubMed
2. Bauer, A., “Total hip replacement – robotic assisted technique,” In: Computer and Robotic Assisted Knee and Hip Surgery (DiGioia, A., ed.) (Oxford University Press, 2004) pp. 83–96.CrossRefGoogle Scholar
3. Siebert, W., Mai, S., Kober, R. and Heeckt, P. F., “Technique and first clinical results of robot-assisted total knee replacement,” Knee, 9 (3), 173–180 (2002).CrossRefGoogle ScholarPubMed
4. Siebert, W., Mai, S., Kober, R. and Heeckt, P., “Total knee replacement: Robot-assistive technique,” In: Computer and Robotic Assisted Knee and Hip Surgery (DiGioia, A., ed.) (Oxford University Press, 2000) pp. 122–135.Google Scholar
5. Davies, B. L., Rodriguez y Baena, F., Barrett, A. R. W., Gomes, M. P. S. F., Harris, S. J., Jakopec, M. and Cobb, J. P., “Robotic control in knee joint replacement surgery,” Proc. Inst. Mech. Eng. H, J. Eng. Med. 221, 71–80 (2007).CrossRefGoogle ScholarPubMed
6. U.S.A. Food and Drug Administration, “Digimatch Robodoc surgical system receives U.S. FDA 510(k) marketing clearance,” NO: K072629 (6 Aug. 2008).Google Scholar
7. Harris, S. J., Arambula-Cosio, F., Mei, Q., Hibberd, R. D., Davies, B. L., Wickham, J. E. A., Nathan, M. S. and Kundu, B., “The Probot – an active robot for prostate resection,” Proc. Inst. Mech. Eng. H, J. Eng. Med. 211 (4), 317–326 (1997).CrossRefGoogle ScholarPubMed
8. Jakopec, M., Harris, S., Rodriguez y Baena, F. M., Gomes, P., Cobb, J. and Davies, B., “The first clinical application of a ‘hands-on’ robotic knee surgery system,” Comp. Aid. Surg. 6 (6), 329–339 (2001).CrossRefGoogle ScholarPubMed
9. Jakopec, M., Rodriguez y Baena, F. M., Harris, S. J., Gomes, P., Cobb, J. and Davies, B. L., “The hands-on orthopaedic robot ‘Acrobot’: Early clinical trials of total knee replacement surgery,” IEEE Trans. Rob. Automat. 19 (5), 902–911 (2003).CrossRefGoogle Scholar
10. Cobb, J., Henckel, J., Gomes, P., Harris, S., Jakopec, M., Rodriguez y Baena, F., Barrett, A. and Davies, B., “Hands-on robotic unicompartmental knee replacement,” J. Bone Joint Surg. 88, 188–197 (2006).CrossRefGoogle ScholarPubMed
11. Guthart, G. S. and Salisbury, J. K., “The Intuitive telesurgery system: Overview and application,” IEEE Int. Conf. Rob. Automat. 1, 618–4102 (2000).Google Scholar
12. Henckel, J., Richards, R., Lozhkin, K., Harris, S., Rodriguez y Baena, F. M., Barrett, A. R. W. and Cobb, J. P., “Very low-dose computed tomography for planning and outcome measurement in knee replacement,” J. Bone Joint Surg. 88, 1513–1518 (2006).CrossRefGoogle ScholarPubMed
13. Barrett, A. R. W., Davies, B. L., Gomes, M. P. S. F., Harris, S. J., Henckel, J., Jakopec, M., Kannan, V., Rodriguez y Baena, F. M. and Cobb, J. P., “Computer-assisted hip resurfacing surgery using the Acrobot navigation system,” Proc. Inst. Mech. Eng. H, J. Eng. Med. 221, 773–786 (2007).CrossRefGoogle ScholarPubMed
14. Barrett, A. R. W., Davies, B. L., Gomes, M. P. S. F., Harris, S. J., Henckel, J., Jakopec, M., Rodriguez y Baena, F. M. and Cobb, J. P., “Preoperative planning and intraoperative guidance for accurate computer-assisted minimally invasive hip resurfacing surgery,” Proc. Inst. Mech. Eng. H, J. Eng. Med. 220, 759–774 (2006).CrossRefGoogle ScholarPubMed
15. Maintz, J. and Viergever, M., “A survey of medical image registration,” Med. Image Anal. 2 (1), 1–36 (1998).CrossRefGoogle ScholarPubMed
16. Ellis, R. E., Toksvig-Larsen, S., Marcacci, M., Caramella, D., and Fadda, M., “Use of a biocompatible fiducial marker in evaluating the accuracy of computed tomography image registration,” Invest. Radiol. 31 (10), 658–667 (1996).CrossRefGoogle ScholarPubMed
17. Leardini, A., “Validation of a functional method for the estimation of hip joint centre location,” J. Biomech. 32 (1), 99 (1999).CrossRefGoogle ScholarPubMed
18. MyungJin, K., Sadri, H., Moccozet, L., Magnenat-Thalmann, N. and Hoffmeyer, P., “Accurate simulation of hip joint range of motion,” In: Computer Animation, 2002. Proceedings (2002) pp. 215–219.Google Scholar
19. Besl, P. and McKay, N., “A method for registration of 3-d shapes,” IEEE Trans. Patt. Anal. Mach. Intell. 14 (2), 239–250 (1992).CrossRefGoogle Scholar
20. Rodriguez y Baena, F., Improving accuracy in robotic assisted orthopaedic surgery Ph.D. Thesis, (London: Imperial College London, 2004).Google Scholar