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Unilaterally Constrained Motion of a Curved Surgical Tool

Published online by Cambridge University Press:  10 January 2020

Bassem Dahroug*
Affiliation:
AS2M Department, FEMTO-ST Institute, Univ. Bourgogne Franche-Comté/CNRS, 24 Rue Alain Savary, 25000 Besançon, France E-mail: [email protected]
Brahim Tamadazte
Affiliation:
AS2M Department, FEMTO-ST Institute, Univ. Bourgogne Franche-Comté/CNRS, 24 Rue Alain Savary, 25000 Besançon, France E-mail: [email protected] Institute for Intelligent Systems and Robotics, University of Sorbonne, CNRS, UMR 7222, 4 place Jussieu, 75005 Paris, France E-mail: [email protected]
Nicolas Andreff
Affiliation:
AS2M Department, FEMTO-ST Institute, Univ. Bourgogne Franche-Comté/CNRS, 24 Rue Alain Savary, 25000 Besançon, France E-mail: [email protected]
*
Corresponding author. E-mail: [email protected]

Summary

Constrained motion is essential for varying robotics tasks, especially in surgical robotics, for instance, the case of minimally invasive interventions. This article proposes generic formulations of the classical bilateral constrained motion (i.e., when the incision hole has almost the same diameter as that of the tool) as well as unilaterally constrained motion (i.e., when the hole incision has a larger diameter compared to the tool diameter). One of the latter constraints is combined with another surgical task such as incision/ablation or suturing a wound (modeled here by 3D geometric paths). The developed control methods based on the hierarchical task approach are able to manage simultaneously the constrained motion (depending on the configuration case, i.e., bilateral or unilateral constraint) and a 3D path following. In addition, the proposed methods can operate with both straight or curved surgical tools. The proposed methods were successfully validated in various scenarios. Foremost, a simulation framework was proposed to access the performances of each proposed controller. Thereafter, several experimental validations were carried out. Both the simulation and experimental results have demonstrated the relevance of the proposed approach, as well as promising performances in terms of behavior as well as accuracy.

Type
Articles
Copyright
Copyright © Cambridge University Press 2020

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Footnotes

*

This work has been supported by the ANR μRoCS Project (ANR-17-CE19-0005-04).

References

Osa, T., Staub, C. and Knoll, A., “Framework of Automatic Robot Surgery System Using Visual Servoing,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan (2010) pp. 1837–1842.Google Scholar
Dalvand, M. M. and Shirinzadeh, B., “Remote Centre-of-Motion Control Algorithms of 6-RRCRR Parallel Robot Assisted Surgery System (PRAMiSS),” IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA (2012) pp. 3401–3406.Google Scholar
Fleming, I., Balicki, M., Koo, J., et al., “Cooperative Robot Assistant for Retinal Microsurgery,International Conference on Medical Image Computing and Computer-Assisted Intervention, New York, NY, USA (2008) pp. 543550.Google Scholar
Ida, Y., Sugita, N., Ueta, T., et al., “Microsurgical robotic system for vitreoretinal surgery,Int. J. Comput. Assist. Radiol. Surgery 7(1), 2734 (2012).CrossRefGoogle Scholar
Taylor, R. H., Funda, J., Grossman, D. D., et al.,“Remote Center-of-Motion Robot for Surgery,” (1995), US Patent 5,397,323.Google Scholar
Dahroug, B., Tamadazte, B. and Andreff, N., “Task Controller for Performing Remote Centre of Motion,” In: Lecture Note on Electrical Engineering (Di Cecco, L., ed.) (Springer, Berlin, Germany, 2017).Google Scholar
Blumentals, A., Brogliato, B. and Bertails-Descoubes, F., “The contact problem in Lagrangian systems subject to bilateral and unilateral constraints, with or without sliding Coulombs friction: A tutorial,Multibody Syst. Dyn. 38(1), 4376 (2016).CrossRefGoogle Scholar
Swaney, P. J., Croom, J. M., Burgner, J., et al., “Design of a Quadramanual Robot for Single-Nostril Skull Base Surgery,” ASME Annual Dynamic Systems and Control Conference, Fort Lauderdale, FL, USA, vol. 3 (2012) pp. 387393.Google Scholar
Girerd, C., Rabenorosoa, K. and Renaud, P., “Combining Tube Design and Simple Kinematic Strategy for Follow-the-Leader Deployment of Concentric Tube Robots,” In: Advances in Robot Kinematics (Lenarčič, J. and Merlet, J. P., eds.) (Springer, Berlin, Germany, 2016) pp. 2331.Google Scholar
Miroir, M., Nguyen, Y., Szewczyk, J., et al., “Robotol: From design to evaluation of a robot for middle ear surgery,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan (2010) pp. 850–856.Google Scholar
Entsfellner, K., Tauber, R., Roppenecker, D. B., et al., “Development of universal gripping adapters: Sterile coupling of medical devices and robots using robotic fingers,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Wollongong, NSW, Australia (2013) pp. 1464–1469.Google Scholar
Dahroug, B., Tamadazte, B., Weber, B., et al., “Review on otological robotic systems: Toward microrobot-assisted cholesteatoma surgery,IEEE Rev. Biomed. Eng. 11(1), 125142 (2018).Google Scholar
Nakamura, Y., Hanafusa, H. and Yoshikawa, T., “Task-priority based redundancy control of robot manipulators,Int. J. Robot. Res. 6(3), 315 (1987).Google Scholar
Siciliano, B., “Kinematic control of redundant robot manipulators: A tutorial,J. Intel. Robot. Syst. 3(3), 201212 (1990).CrossRefGoogle Scholar
Mansard, N. and Khatib, O., “Continuous Control Law from Unilateral Constraints,” IEEE International Conference on Robotics and Automation, Pasadena, CA, USA (2008) pp. 3359–3364.Google Scholar
Kuo, C.-H., Dai, J. S. and Dasgupta, P., “Kinematic design considerations for minimally invasive surgical robots: An overview,Int. J. Med. Robot. Comput. Assist. Surg. 8(2), 127145 (2012).Google Scholar
Funda, J., Taylor, R. H., Eldridge, B., et al., “Constrained cartesian motion control for teleoperated surgical robots,IEEE Trans. Robot. Autom. 12(3), 453465 (1996).Google Scholar
Azimian, H., Patel, R. V., and Naish, M. D., “On Constrained Manipulation in Robotics-Assisted Minimally Invasive Surgery,” IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, Tokyo, Japan (2010) pp. 650–655.Google Scholar
Marinho, M. M., Bernardes, M. C. and , A. P., “A Programmable Remote Center-of-Motion Controller for Minimally Invasive Surgery Using the Dual Quaternion Framework,” IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, Sao Paulo, Brazil (2014) pp. 339–344.Google Scholar
Pham, C. D., Coutinho, F., Leite, A. C., et al., “Analysis of a Moving Remote Center of Motion for Robotics-Assisted Minimally Invasive Surgery,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany (2015) pp. 1440–1446.Google Scholar
Mayer, H., Nagy, I. and Knoll, A., “Kinematics and Modelling of a System for Robotic Surgery,” In: Advances in Robot Kinematics (Lenarčič, J. and Galletti, C., eds.) (Springer, Berlin, Germany, 2004) pp. 181190.Google Scholar
Boctor, E. M., R. J. Webster, III, Mathieu, H., et al., “Virtual remote center of motion control for needle placement robots,Comput. Aid. Surg. 9(1), 175183 (2004).Google Scholar
Dahroug, B., Seon, J. A., Oulmas, A., Xu, T., Tamadazte, B., et al., “Some Examples of Path Following in Microrobotics,” IEEE International Conference on Manipulation, Automation and Robotics at Small Scales, Nagoya, Japan (2018) pp. 16.Google Scholar
Rosenberg, L. B., “Virtual Fixtures: Perceptual Tools for Telerobotic Manipulation,” IEEE Virtual Reality Annual International Symposium, Seattle, WA, USA (1993) pp. 76–82.Google Scholar
Bowyer, S. A., Davies, B. L. and y Baena, F. R., “Active constraints/virtual fixtures: A survey,” IEEE Trans. Robot. 30(1), 138157 (2014).Google Scholar
Dahroug, B., Tamadazte, B. and Andreff, N., “Visual Servoing Controller for Time-Invariant 3D Path Following with Remote Centre of Motion Constraint,” IEEE International Conference on Robotics and Automation, Singapore (2017) pp. 3612–3618.Google Scholar
Marchand, E., Spindler, F. and Chaumette, F., “Visp for Visual Servoing: A Generic Software Platform with a Wide Class of Robot Control Skills,IEEE Robot. Autom. Mag. 12(4), 4052 (2005).Google Scholar
Kazemi, M., Gupta, K. and Mehrandezh, M., “Path-Planning for Visual Servoing: A Review and Issues,” In: Visual Servoing via Advanced Numerical Methods (Chesi, G., ed.) (Springer, Berlin, Germany, 2010) pp. 189207.Google Scholar
Gerber, N., Bell, B., Gavaghan, K., et al., “Surgical planning tool for robotically assisted hearing aid implantation,Int. J. Comput. Assist. Radio. Surg. 9(1), 1120 (2014).CrossRefGoogle Scholar
Gasparetto, A., Boscariol, P., Lanzutti, A. and Vidoni, R., “Path Planning and Trajectory Planning Algorithms: A General Overview,” In: Motion and Operation Planning of Robotic Systems (Carbone, G. and Gomez-Bravo, F., eds.) (Springer, Berlin, Germany, 2015) pp. 327.Google Scholar
Seon, J. A., Tamadazte, B. and Andreff, N., “Decoupling path following and velocity profile in vision-guided laser steering,IEEE Trans. Robot. 31(2), 280289 (2015).Google Scholar
Renevier, R., Tamadazte, B., Rabenorosoa, K., et al., “Endoscopic laser surgery: Design, modeling, and control,IEEE/ASME Trans. Mechatron. 22(1), 99106 (2017).Google Scholar
Tamadazte, B., Renevier, R., Séon, J., et al., “Laser beam steering along three-dimensional paths,IEEE/ASME Trans. Mechatron. 23(3), 11481158 (2018).Google Scholar