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Collaborative Human–Robot Interaction Interface: Development for a Spinal Surgery Robotic Assistant

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Abstract

The growing introduction of robotics in non-industrial applications where the environment is unstructured and changing, has led to the need of development of safer and more intuitive, human–robot interfaces. In such environments, the use of collaborative robots has potential benefits, due to the combination of user experience, knowledge and flexibility with the robot’s accuracy, stiffness and repeatability. Nevertheless, in order to guarantee a functional collaboration in these environments, the interaction between user and robot must be intuitive, natural, fast and easy to use. On one hand, commercial collaborative robots are less accurate and less stiff than the traditional industrial ones, on the other hand, the later have not intuitive interaction interfaces. There are tasks in which the stiffness of industrial robots and the intuitive interaction interfaces of collaborative commercial robots, are desirable. This is the case of some robotic assisted surgical procedures, such as robotic assisted spine surgery, with high accuracy demands and with the need of intuitive surgeon–robot interaction. This paper presents a hand guiding methodology for functional human–robot collaboration and the introduction of novel algorithms to enhance its behavior. Also its implementation on a robotic surgical assistant for spine procedures is presented. It is emphasized how a traditional industrial robot can be used as a collaborative one when the available commercial collaborative robots do not have the required accuracy and stiffness for the task.

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References

  1. Neto P, Mendes N (2013) Direct off-line robot programming via a common CAD package. Robot Auton Syst 61:896–910. https://doi.org/10.1016/j.robot.2013.02.005

    Article  Google Scholar 

  2. Aliaga I, Rubio A, Sanchez E (2004) Experimental quantitative comparison of different control architectures for master–slave teleoperation. IEEE Trans Control Syst Technol 12(1):2–11. https://doi.org/10.1109/TCST.2003.819586

    Article  Google Scholar 

  3. Chen J, Haas E, Barnes M (2007) Human performance issues and user interface design for teleoperated robots. IEEE Trans Syst Man Cybern C Appl Rev 37(6):1231–1245. https://doi.org/10.1109/TSMCC.2007.905819

    Article  Google Scholar 

  4. Sathiyanarayanan M, Azharuddin S, Kumar S et al (2014) Gesture controlled robot for military purpose. Int J Technol Res Eng 1(11):1300–1303

    Google Scholar 

  5. Anurag M, Pooja M, Akshay K et al. (July 2015) A voice-controlled personal assistant robot. In: International conference on industrial instrumentation and control. https://doi.org/10.1109/IIC.2015.7150798

  6. Hanses M, Behrens R, Elkmann N (2016) Hand-guiding robots along predefined geometric paths under hard joint constraints. In: IEEE international conference on emerging technologies and factory automation. https://doi.org/10.1109/ETFA.2016.7733600

  7. Calzado J, Lindsay A, Chen C et al (2018) SAMI : interactive, multi-sense robot architecture. In: 2018 IEEE 22nd international conference on intelligent engineering systems (INES), pp 317–322. https://doi.org/10.1109/INES.2018.8523933

  8. De Santis A, Siciliano B, De Luca A et al (2008) An atlas of physical human–robot interaction. Mech Mach Theory 43(3):253–270. https://doi.org/10.1016/j.mechmachtheory.2007.03.003

    Article  MATH  Google Scholar 

  9. Labrecque P, Gosselin C (2017) Variable Admittance for pHRI: from intuitive unilateral interaction to optimal bilateral force Amplification. Robot Comput-Integ Manuf 52:1–8. https://doi.org/10.1016/j.rcim.2018.01.005

    Article  Google Scholar 

  10. Ostergaard EH (2012) Lightweight robot for everybody. Robot Autom Mag 19:17–18. https://doi.org/10.1109/MRA.2012.2221279

    Article  Google Scholar 

  11. Keeping S (2018) Designing collaborative robots. Collaborative robotics EIT eBOOK 2(1)

  12. Hipol P (2018) Technologies converge to help drive manufacturing applications. Collab Robot EIT eBOOK 2(1):19–20

    Google Scholar 

  13. Jubien A, Gautier M, Janot A (2014) Dynamic identification of the Kuka LightWeight robot: Comparison between actual and confidential Kuka’s parameters. In: IEEE/ASME international conference on advanced intelligent mechatronics, AIM. pp 483–488. https://doi.org/10.1109/AIM.2014.6878124

  14. hu M, Wang H, Pan X (2019) An extended stiffness model for 7 Dofs collaborative robots using the virtual joint method. In: IEEE international conference on robotics and biomimetics, ROBIO 2019, pp 1653–1658. https://doi.org/10.1109/ROBIO49542.2019.8961548

  15. Keemink A, Van der Kooij H, Stienen A (2018) Admittance control for physical human–robot interaction. 37(11):1421–1444. https://doi.org/10.1177/0278364918768950

  16. Melo J, Bertelsen A, Borro D et al (2012) Nuevo asistente robótico para cirugía: Arquitectura y algoritmos de control. 87(6):645–654. https://doi.org/10.6036/5011

  17. Craig J (2005) Introduction to robotics. Mechanics and control, 3rd edn. 2005 Pearson education. ISBN 0-13-123629-6

  18. Safeea M, Neto P (2018) End-e ector precise hand-guiding for collaborative robots. In: ROBOT 2017: third Iberian robotics conference. https://doi.org/10.1007/978-3-319-70833-1

  19. Melo-Uribe J, Bertelsen-Simonetti A, Borro-Yagüez D et al (2012) New robotic surgical assistant: architecture and control algorithms. DYNA 87:647–654. https://doi.org/10.6036/5011

    Article  Google Scholar 

  20. Antonelli G, Chiaverini S, Fusco G (2003) A new on-line algorithm for inverse kinematics of robot manipulators ensuring path tracking capability under joint limits. IEEE Trans Robot Autom 19(1):162–167. https://doi.org/10.1109/TRA.2002.807543

    Article  Google Scholar 

  21. Ben-Israel A (2002) The Moore of the Moore-Penrose inverse. The Electron J of Linear Algebra 9(1):150–157. https://doi.org/10.13001/1081-3810.1083

    Article  MathSciNet  MATH  Google Scholar 

  22. Siciliano B (1990) A closed-loop inverse kinematic scheme for on-line joint-based robot control. Robotica 8(1):231–243. https://doi.org/10.1017/s0263574700000096

    Article  Google Scholar 

  23. Gray Henry (1918) The vertebral column. In Anatomy of the Human Body, chapter 3

  24. Frost B, Camarero-Espinoza S, Johan Foster E (2019) Materials for the spine: Anatomy, problems, and solutions. Materials 12(2):1–41. https://doi.org/10.3390/ma12020253

    Article  Google Scholar 

  25. Ravindra Vijay M et al (2018) Degenerative lumbar spine disease: estimating global incidence and worldwide. Glob Spine J 8(8):784–794

    Article  Google Scholar 

  26. Raciborski F, Gasik R, Kłak A (2016) Disorders of the spine. A major health and social problem. Rheumatol J 54(4):196–200. https://doi.org/10.5114/reum.2016.62474

    Article  Google Scholar 

  27. Moran JM, Berg WS et al (1989) Transpedicular screw fixation. J Orthop Res 7(1):107–114. https://doi.org/10.1002/jor.1100070115

    Article  Google Scholar 

  28. Morales-Ávalos R, Elizondo-Omaña R, Vílchez-Cavazos F et al (2012) Fijación vertebral por vía transpedicular. Importancia de los estudios anatómicos y de imagen. Acta Ortopédica Mexicana 26(6):402–411

    Google Scholar 

  29. Puvanesarajah V (2014) Techniques and accuracy of thoracolumbar pedicle screw placement. World J Orthopedics 5(2):112. https://doi.org/10.5312/wjo.v5.i2.112

    Article  Google Scholar 

  30. Puvanesarajah V, Liauw J, Lo S et al (2014) Techniques and accuracy of thoracolumbar pedicle screw placement. World J Orthopedy 5(2):112–123

    Article  Google Scholar 

  31. Scheufler KM, Franke J, Eckardt A et al (2011) Accuracy of image-guided pedicle screw placement using intraoperative computed tomography-based navigation with automated referencing. Neurosurg J 69(6):1307–1316. https://doi.org/10.1227/NEU.0b013e31822ba190

    Article  Google Scholar 

  32. Schizas C, Thein E, Kwiatkowsk B et al (2012) Pedicle screw insertion: robotic assistance versus conventional c-arm fluoroscopy. Belgian Orthopedic Act 78(2):240–5

    Google Scholar 

  33. Overley S, Cho S et al (2017) Navigation and robotics in spinal surgery: Where are we now? Clin Neurosurg J 80(3):586–599 10.1093/neuros/nyw077

    Google Scholar 

  34. Amarillo A, Sanchez E, Suarez C et al (2017) Diseño cinemático de dispositivo de tracking del paciente para procedimientos quirúrgicos. XXXV Congreso Anual de la Sociedad Espanola de Ingeniería Biomedica, pp 275–278. ISBN: 978-84-9082-797-0

  35. Amarillo A, Oñativia J, Sanchez E (2018) RoboTracker: collaborative robotic assistant device with electromechanical patient tracking for spinal surgery. In: 2018 IEEE/RSJ international conference on intelligent robots and systems, pp 1312–1317. https://doi.org/10.1109/IROS.2018.8594467

  36. Puvanesarajah V (2015) Techniques and accuracy of thoracolumbar pedicle screw placement. World J Orthopedics 5(2):112–123. https://doi.org/10.5312/wjo.v5.i2.112

    Article  Google Scholar 

  37. Bertrelsen A (2013) Planning and registration techniques for image-guided robotic spinal surgery. PhD thesis. Universidad de Navarra. ISBN: 978-84-8081-342-6

  38. Bertrelsen A, Garin-Muga A et al (2014) Distortion correction and calibration of intra-operative spine X-ray images using a constrained DLT algorithm. Comput Med Imaging Graph 38(7):558–568. https://doi.org/10.1016/j.compmedimag.2014.06.004

    Article  Google Scholar 

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Acknowledgements

The present research work was possible thanks to the ROBOTRACKER(Basque government, GAITEK IG-2015/0000782), ELCANO (Spanish goverment founding, INNPACTO IPT-2012-0508-300000) and MAXILARIS (Spanish goverment, RETOS RTC-2015-3871-1) projects, and the people who have worked on them, they deserve sincere thanks for the contributions that have provided. The authors declare that they have no conflict of interest.

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Amarillo, A., Sanchez, E., Caceres, J. et al. Collaborative Human–Robot Interaction Interface: Development for a Spinal Surgery Robotic Assistant. Int J of Soc Robotics 13, 1473–1484 (2021). https://doi.org/10.1007/s12369-020-00733-x

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