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An Energy-Based Approach for n-d.o.f. Passive Dual-User Haptic Training Systems

Published online by Cambridge University Press:  30 August 2019

Fei Liu ,
Angel Ricardo Licona ,
Arnaud Lelevé Open the ORCID record for Arnaud Lelevé [Opens in a new window] ,
Damien Eberard ,
Minh Tu Pham  and
Tanneguy Redarce
Fei Liu
Affiliation:
Center for Micro-BioRobotics IIT@SSSA, Italy
Angel Ricardo Licona
Affiliation:
Ampère (CNRS UMR 5005), Université de Lyon, INSA Lyon, F69621 Villeurbanne, France
Arnaud Lelevé*
Affiliation:
Center for Micro-BioRobotics IIT@SSSA, Italy
Damien Eberard
Affiliation:
Ampère (CNRS UMR 5005), Université de Lyon, INSA Lyon, F69621 Villeurbanne, France
Minh Tu Pham
Affiliation:
Ampère (CNRS UMR 5005), Université de Lyon, INSA Lyon, F69621 Villeurbanne, France
Tanneguy Redarce
Affiliation:
Ampère (CNRS UMR 5005), Université de Lyon, INSA Lyon, F69621 Villeurbanne, France
*
*Corresponding author. E-mail: arnaud.leleve@insa-lyon.fr
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Summary

This paper introduces a dual-user training system whose design is based on an energetic approach. This kind of system is useful for supervised hands-on training where a trainer interacts with a trainee through two haptic devices, in order to practice on a manual task performed on a virtual or teleoperated robot (e.g., for an Minimally Invasive Surgery (MIS) task in a surgical context). This paper details the proof of stability of an Energy Shared Control (ESC) architecture we previously introduced for one degree of freedom (d.o.f.) devices. An extension to multiple degrees of freedom is proposed, along with an enhanced version of the Adaptive Authority Adjustment function. Experiments are carried out with 3 d.o.f. haptic devices in free motion as well as in contact contexts in order to show the relevance of this architecture.

Keywords

Computer simulationDual-user systemHands-on trainingHaptic interfacesPort-Hamiltonian frameworkShared control
Type
Articles
Information
Robotica , Volume 38 , Issue 7 , July 2020 , pp. 1155 - 1175
Copyright
© Cambridge University Press 2019

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References

Vaughan, N., Dubey, V. N., Wee, M. Y. and Isaacs, R., “A review of epidural simulators: Where are we today?” Med. Eng. Phys. 35(9), 1235–1250 (2013).CrossRefGoogle ScholarPubMed
Yiannakopoulou, E., Nikiteas, N., Perrea, D. and Tsigris, C., “Virtual reality simulators and training in laparoscopic surgery”, Int. J. Sur. 13(9), 60–64 (2014).CrossRefGoogle ScholarPubMed
Delorme, S., Laroche, D., DiRaddo, R. and Del Maestro, R. F., “Neurotouch: A physics-based virtual simulator for cranial microneurosurgery training”, Neurosurgery 71, 32–42 (2012).Google ScholarPubMed
Panait, L., Akkary, E., Bell, R., Roberts, K., Dudrick, S. and Duffy, A., “The role of haptic feedback in laparoscopic simulation training”, J. Surg. Res. 156(2), 312–316 (2009).CrossRefGoogle ScholarPubMed
Talasaz, A., Trejos, A. L. and Patel, R. V., “The role of direct and visual force feedback in suturing using a 7-dof dual-arm teleoperated system”, IEEE Trans. Hapt. 10(2), 276–287 (2017).CrossRefGoogle ScholarPubMed
Chebbi, B., Lazaroff, D. and Liu, P. X., “A collaborative virtual haptic environment for surgical training and tele-mentoring”, Int. J. Robot. Autom. 22(1), 69–78 (2007).Google Scholar
Liu, F., Lelevé, A., Eberard, D. and Redarce, T., “A Dual-User Teleoperation System with Online Authority Adjustment for Haptic Training,” Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC15), Milano, Italy (2015).CrossRefGoogle Scholar
Stramigioli, S., Modeling and IPC Control of Interactive Mechanical Systems: A Coordinate-Free Approach (Springer, London, UK, 2001).Google Scholar
Liu, F., Lelevé, A., Eberard, D. and Redarce, T., “A Dual-User Teleoperation System with Adaptive Authority Adjustment for Haptic Training,” Proceedings of 4th International Workshop on Medical and Service Robots, Bergamo, Italy (2015).CrossRefGoogle Scholar
Khademian, B. and Hashtrudi-Zaad, K., “Shared control architectures for haptic training: Performance and coupled stability analysis”, Int. J. Robot. Res. 30(13), 1627–1642 (2011).CrossRefGoogle Scholar
Liu, F., Lelevé, A., Eberard, D. and Redarce, T., “An Energy Based Approach for Passive Dual-User Haptic Training Systems,” Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2016), Daejeon, South Korea (2016).CrossRefGoogle Scholar
Licona, A. R., Liu, F., Lelevé, A., Eberard, D. and Pham, M. T., “Collaborative Hands-on Training on Haptic Simulators,” Proceedings of the 2019 3rd International Conference on Virtual and Augmented Reality Simulations, Perth, Australia (2018) pp. 39–45.Google Scholar
Nudehi, S., Mukherjee, R. and Ghodoussi, M., “A shared-control approach to haptic interface design for minimally invasive telesurgical training”, IEEE Trans. Control Syst. Tech. 13(4), 588–592 (2005).CrossRefGoogle Scholar
Ghorbanian, A., Rezaei, S., Khoogar, A., Zareinejad, M. and Baghestan, K., “A novel control framework for nonlinear time-delayed dual-master/single-slave teleoperation”, ISA Trans. 52(2), 268–277 (2013).CrossRefGoogle ScholarPubMed
Razi, K. and Hashtrudi-Zaad, K., “Analysis of coupled stability in multilateral dual-user teleoperation systems”, IEEE Trans. Robot. 30(3), 631–641 (2014).CrossRefGoogle Scholar
Shamaei, K., Kim, L. and Okamura, A., “Design and Evaluation of a Trilateral Shared-Control Architecture for Teleoperated Training Robots,” 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milano, Italy (2015) pp. 4887–4893.Google Scholar
Shahbazi, M., Talebi, H., Atashzar, S., Towhidkhah, F., Patel, R. and Shojaei, S., “A New Set of Desired Objectives for Dual-User Systems in the Presence of Unknown Communication Delay,” 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Budapest, Hungary (2011) pp. 146–151.Google Scholar
Nuño, E., Basañez, L. and Ortega, R., “Passivity-based control for bilateral teleoperation: A tutorial”, Automatica 47(3), 485–495 (2011).CrossRefGoogle Scholar
Lee, D. and Li, P., “Passive bilateral feedforward control of linear dynamically similar teleoperated manipulators”, IEEE Trans. Robot. Auto. 19(3), 443–456 (2003).Google Scholar
Lee, D. and Spong, M., “Passive bilateral teleoperation with constant time delay”, IEEE Trans. Robot. 22(2), 269–281 (2006).CrossRefGoogle Scholar
Lu, Z., Huang, P., Dai, P., Liu, Z. and Meng, Z., “Enhanced transparency dual-user shared control teleoperation architecture with multiple adaptive dominance factors”, Int. J. Control Auto. Syst. 15(5), 2301–2312 (2017).CrossRefGoogle Scholar
Zakerimanesh, A., Hashemzadeh, F. and Ghiasi, A. R., “Dual-user nonlinear teleoperation subjected to varying time delay and bounded inputs”, ISA Trans. 68, 33–47 (2017).CrossRefGoogle ScholarPubMed
Beltran-Carbajal, F., Advances in Vibration Engineering and Structural Dynamics (InTech, 2012).CrossRefGoogle Scholar
Shahbazi, M., Atashzar, S., Talebi, H. and Patel, R., “An Expertise-Oriented Training Framework for Robotics-Assisted Surgery,” 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China (2014) pp. 5902–5907.Google Scholar
van der Schaft, A. and Jeltsema, D., “Port-Hamiltonian systems theory: An introductory overview”, Found. Trends Syst. Control 1(2–3), 173–378 (2014).CrossRefGoogle Scholar
Duindam, V., Macchelli, A., Stramigioli, S. and Bruyninckx, H., Modeling and Control of Complex Physical Systems: The Port-Hamiltonian Approach (Springer, Berlin/Heidelberg, Germany, 2009).CrossRefGoogle Scholar
Sansanayuth, T., Nilkhamhang, I. and Tungpimolrat, K., “Teleoperation with Inverse Dynamics Control for Phantom Omni Haptic Device,” Proceedings of SICE Annual Conference (SICE’12), Akita (2012) pp. 2121–2126.Google Scholar
Aldana, C. I., Nuño, E., Basañez, L. and Romero, E., “Operational space consensus of multiple heterogeneous robots without velocity measurements”, J. Franklin Inst. 351(3), 1517–1539 (2014).CrossRefGoogle Scholar
Stramigioli, S., “Creating Artificial Damping by Means of Damping Injection,” Proceedings of the ASME Dynamic Systems and Control Division, New York, NY (1996) pp. 601–606.Google Scholar
Raghu Prasad, M. S., Purswani, S. and Manivannan, M., “Force JND for Right Index Finger Using Contra Lateral Force Matching Paradigm,” In: Proceedings of the Conference ICoRD’13 (Chakrabarti, A. and Prakash, R. V., eds.) (Springer, India, 2013) pp. 365–375.Google Scholar