Towards Cognitive Medical Robotics in Minimal Invasive Surgery

ABSTRACT

Up to date, medical robots for minimal invasive surgery do not provide assistance appropriate to the workflow of the intervention. A simple concept of a cognitive system is presented, which is derived from a classic closed-loop control. As implementation, we present a cognitive medical robot system using lightweight robots with redundant kinematics. The robot system includes several control modes and human-machine interfaces. We focus on describing knowledge acquisition about the workflow of an intervention and present two example applications utilizing the acquired knowledge: autonomous camera guidance and planning of minimal invasive port (trocar) positions in combination with an initial robot setup. Port planning is described as optimization problem. The autonomous camera system includes a mid-term movement prediction of the ongoing intervention. The cognitive approach to a medical robot system includes taking the environment into account. The goal is to create a system that acts as a human assistant, who perceives the situation, understands the context based on his knowledge and acts appropriate.

References

1. L. Adhami. An architecture for computer integrated minimal-invasive surgery: focus on optimal planning. PhD thesis, Paris: Ècole des Mines de Paris, 2002.
2. J. R. Anderson. The architecture of cognition, volume 5. Lawrence Erlbaum, 1995.
3. A. Casals, J. Amat, and E. Laporte. Automatic guidance of an assistant robot in laparoscopic surgery. In Robotics and Automation, 1996. Proc 1996 IEEE Int Conf on, volume 1, pages 895--900. IEEE, 1996.
4. È. Coste-Manière, L. Adhami, F. Mourgues, and A. Carpentier. Planning, simulation, and augmented reality for robotic cardiac procedures: The stars system of the chir team. In Seminars in thoracic and cardiovascular surgery, volume 15, pages 141--156. Elsevier, 2003.
5. H. Feußner, S. Can, A. Fiolka, A. Schneider, and D. Wilhelm. Leistungsfähigkeit, risiken und vorteile des einsatzes der robotik in medizinisch-operativen disziplinen. Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz, 53(8):831--838, 2010.
6. U. Hagn, M. Nickl, S. Jörg, G. Passig, T. Bahls, A. Nothhelfer, F. Hacker, L. Le-Tien, A. Albu-Schäffer, R. Konietschke, et al. The DLR MIRO: a versatile lightweight robot for surgical applications. Industrial Robot: An Int Journal, 35(4):324--336, 2008.
7. J. H. Holland. Studying complex adaptive systems. Journal of Systems Science and Complexity, 19(1):1--8, 2006.
8. D. Katić, G. Sudra, S. Speidel, G. Castrillon-Oberndorfer, G. Eggers, and R. Dillmann. Knowledge-based situation interpretation for context-aware augmented reality in dental implant surgery. Medical Imaging and Augmented Reality, pages 531--540, 2010.
9. S.-Y. Ko, J. Kim, W.-J. Lee, and D.-S. Kwon. Surgery task model for intelligent interaction between surgeon and laparoscopic assistant robot. Int Journal of Assitive Robotics and Mechatronics, 8(1):38--46, 2007.
10. S.-Y. Ko and D.-S. Kwon. A surgical knowledge based interaction method for a laparoscopic assistant robot. In Robot and Human Interactive Communication, 2004. ROMAN 2004. 13th IEEE Int Workshop on, pages 313--318. IEEE, 2004.
11. R. Konietschke. Planning of Workplaces with Multiple Kinematically Redundant Robots. PhD thesis, Ph. D. dissertation, Munich, Germany, 2007, http://nbn-resolving.de/urn/resolver. pl, 2007.
12. C. Ledermann, J. Hergenhan, O. Weede, and H. Woern. Combining shape sensor and haptic sensors for highly flexible single port system using fiber bragg sensor technology. In Mechatronics and Embedded Systems and Applications (MESA), 2012 IEEE/ASME Int Conf on, pages 196--201. IEEE, 2012.
13. H. Mönnich, P. Nicolai, T. Beyl, J. Raczkowsky, and H. Wörn. A supervision system for the intuitive usage of a telemanipulated surgical robotic setup. In Robotics and Biomimetics, 2011 IEEE Int Conf on, pages 449--454. IEEE, 2011.
14. P. Nicolai, T. Beyl, H. Mönnich, J. Raczkowsky, and H. Wörn. Op:Sense - an integrated rapid development environment in the context of robot assisted surgery and operation room sensing. In Robotics and Biomimetics, 2011 IEEE Int Conf on, pages 2421--2422. IEEE, 2011.
15. A. Trejos and R. Patel. Port placement for endoscopic cardiac surgery based on robot dexterity optimization. In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE Int Conf on, pages 912--917. IEEE, 2005.
16. O. Weede, F. Dittrich, H. Wörn, B. Jensen, A. Knoll, D. Wilhelm, M. Kranzfelder, A. Schneider, and H. Feussner. Workflow analysis and surgical phase recognition in minimally invasive surgery. In 2012 IEEE Int Conf on Robotics and Biomimetics, Dec 11--14, 2012, Guangzhou, China, 2012.
17. O. Weede, A. Kettler, and H. Wörn. Seed throwing optimization: A probabilistic technique for multimodal function optimization. In Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, 2009. COMPUTATIONWORLD'09. Computation World:, pages 515--519. IEEE, 2009.
18. O. Weede, M. Mehrwald, and H. Woern. Knowledge-based system for port placement and robot setup optimization in minimally invasive surgery. In Robot Control, volume 10, pages 722--728, 2012.
19. O. Weede, H. Mönnich, B. Müller, and H. Wörn. An intelligent and autonomous endoscopic guidance system for minimally invasive surgery. In Robotics and Automation (ICRA), 2011 IEEE Int Conf on, pages 5762--5768. IEEE, 2011.
20. O. Weede, S. Zimmermann, B. Hein, and H. Wörn. Evaluation of seed throwing optimization meta heuristic in terms of performance and parallelizability. In FUTURE COMPUTING 2011, The Third Int Conf on Future Computational Technologies and Applications, pages 92--99, 2011.

Index Terms

• Applied computing

  • Life and medical sciences

    • Health care information systems

  • Operations research

    • Industry and manufacturing

      • Command and control