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Validation of Three KUKA Agilus Robots for Application in Neurosurgery

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Advances in Service and Industrial Robotics (RAAD 2017)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 49))

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Abstract

In this paper, we verify three different 6 degrees of freedom Kuka Agilus robots for application in neurosurgery. Application specific reachability maps are generated for robots with 707 mm (R700), 901 mm (R900), and 1101 mm (R1100) horizontal reach. The reachability of each robot reflects a working volume of a standard stereotactic frame which utilizes the center of arc principle. A working volume with 100% reachability yield has been identified for the R900 and R1100 robots when the robot is positioned sideways to the patient. The R700 robot doesn’t have a 100% reachability yield work volume. Robot configurations within the reachability map are further optimized given two dexterity performance indices: the condition number and a new fuzzy joint limit avoidance function. In the experiments, we have further evaluated the impact on robot work volume given robot orientation with respect to the patient. After reorienting the robot a significant increase in work volume with 100% reachability yield was obtained for all three robots.

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References

  1. Kwoh YS, Hou J, Jonckheere EA, Hayati S (1988) A robot with improved absolute po-sitioning accuracy for CT guided stereotactic brain surgery. IEEE Trans Bio-med Eng 35(2):153–160

    Article  Google Scholar 

  2. Haidegger T, Benyó Z (2008) Industrial robotic solutions for interventional medicine. In: Proceedings of the international GTE conference manufacturing, pp 125–130

    Google Scholar 

  3. Maciunas RJ, Galloway RL, Latimer JW (1994) The application accuracy of stereotactic frames. Neurosurgery 35(4):682–695

    Article  Google Scholar 

  4. Nubiola A, Bonev IA (2013) Absolute calibration of an ABB IRB 1600 robot using a laser tracker. Robot Comput Integr Manufact. 29(1):236–245

    Article  Google Scholar 

  5. Haidegger T, Rudas IJ (2014) From concept to market: surgical robot development. In: Handbook of research on advancements in robotics and mechatronics, vol 242

    Google Scholar 

  6. von Tiesenhausen C (2016) KUKA LBR Med Overview, Augsburg, Germany

    Google Scholar 

  7. González-Martínez J et al (2016) Technique, results, and complications related to robot-assisted stereoelectroencephalography. Neurosurgery 78(2):169–180

    Article  Google Scholar 

  8. Faria C, Erlhagen W, Rito M, De Momi E, Ferrigno G, Bicho E (2015) Review of robotic technology for stereotactic neurosurgery. IEEE Rev Biomed Eng 8:125–137

    Article  Google Scholar 

  9. Deacon G, Harwood A, Holdback J, Maiwand D, Pearce M, Reid I et al (2010) The Pathfinder image-guided surgical robot. Proc Inst Mech Eng Part H J Eng Med 224(5):691–713

    Article  Google Scholar 

  10. Burkart A, Debski RE, McMahon PJ, Rudy T, Fu FH, Musahl V et al (2001) Precision of ACL tunnel placement using traditional and robotic techniques. Comput Aided Surg 6(5):270–278

    Article  Google Scholar 

  11. Jerbić B, Nikolić G, Chudy D, Švaco M, Šekoranja B (2015) Robotic application in neurosurgery using intelligent visual and haptic interaction. Int J Simul Model 14(1):71–84

    Article  Google Scholar 

  12. Liu Y, Tian Z, Hui R et al (2016) Clinical application of Remebot stereotactic surgery system without frame. Chin J Sur 54(5):389–390

    Google Scholar 

  13. Spine Health Institute: Dr. Patel performs groundbreaking robotic surgery in Switzerland. http://www.thespinehealthinstitute.com/news-room/health-blog-news/dr-patel-performs-groundbreaking-robotic-surgery-in-switzerland. Accessed 6 Mar 2016

  14. Lefranc M, Peltier J (2016) Evaluation of the ROSATM Spine robot for minimally invasive surgical procedures. Expert Rev Med Devices 13(10):899–906

    Article  Google Scholar 

  15. Minchev G, Kronreif G, Martínez-Moreno M, Dorfer C, Micko A, Mert A et al (2016) A novel miniature robotic guidance device for stereotactic neurosurgical interventions: preliminary experience with the iSYS1 robot. J Neurosurg 1–12

    Google Scholar 

  16. Briot S, Baradat C, Guégan S, Arakelian V (2007) Contribution to the Mechanical Behavior Improvement of the Robotic Navigation Device Surgiscope, pp 653–661

    Google Scholar 

  17. Cardinale F, Cossu M, Castana L, Casaceli G, Schiariti MP, Miserocchi A et al (2013) Stereoelectroencephalography: surgical methodology, safety, and stereotactic application accuracy in 500 procedures. Neurosurgery 72(3):353–366

    Article  Google Scholar 

  18. Shoham M et al (2007) Robotic assisted spinal surgery–from concept to clinical practice. Comput Aided Surg 12(2):105–115

    Google Scholar 

  19. Heinig M, Hofmann UG, Schlaefer A (2012) Calibration of the motor-assisted robotic stereotaxy system: MARS. Int J Comput Assist Radiol Surg 7(6):911–920

    Article  Google Scholar 

  20. Gasparetto A, Zanotto V (2010) Toward an optimal performance index for neurosurgical robot’s design. Robotica 28(2):279

    Article  Google Scholar 

  21. Vidakovic J, Jerbić B, Šuligoj F, Švaco M, Šekoranja B (2016) Simulation for robotic stereotactic neurosurgery. In: 27th DAAAM

    Google Scholar 

  22. Diankov R, Kuffner J (2008) Openrave: a planning architecture for autonomous robotics. Robotics Institute, Pittsburgh, PA, Technical report CMU-RI-TR-08-34, vol 79

    Google Scholar 

  23. Zacharias F, Borst C, Beetz M, Hirzinger G (2008) Positioning mobile manipulators to perform constrained linear trajectories. In: IEEE/RSJ international conference on intelligent robots and systems, IROS 2008, pp 2578–2584

    Google Scholar 

  24. Khan WA, Angeles J (2006) The kinetostatic optimization of robotic manipulators: the inverse and the direct problems. J Mech Des 128(1):168

    Article  Google Scholar 

  25. Pamanes-Gareia J (1990) A criterion for the optimal placement of robotic manipulators. In: Information control problems in manufacturing technology 1989, 6th IFAC/IFIP/IFORS/IMACS symposium, Madrid, Spain, p 149

    Google Scholar 

  26. Švaco M, Jerbić B, Šuligoj F (2014) Autonomous robot learning model based on visual interpretation of spatial structures. Trans FAMENA 38(4):13–28

    Google Scholar 

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Acknowledgements

Authors would like to acknowledge the Croatian Scientific Foundation through the research project ACRON - A new concept of Applied Cognitive RObotics in clinical Neuroscience. Authors would like to thank the entire team from the hospital Dubrava (KB Dubrava), especially prof. dr. sc. Darko Chudy and Domagoj Dlaka for their help in the clinical procedures.

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Correspondence to Marko Švaco .

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Švaco, M., Koren, P., Jerbić, B., Vidaković, J., Šekoranja, B., Šuligoj, F. (2018). Validation of Three KUKA Agilus Robots for Application in Neurosurgery. In: Ferraresi, C., Quaglia, G. (eds) Advances in Service and Industrial Robotics. RAAD 2017. Mechanisms and Machine Science, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-61276-8_107

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  • DOI: https://doi.org/10.1007/978-3-319-61276-8_107

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-61276-8

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