Hostname: page-component-7f64f4797f-42qgm Total loading time: 0 Render date: 2025-11-04T14:43:46.331Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamics Modeling of Human–Machine Control Interface for Underwater Teleoperation

Published online by Cambridge University Press:  22 July 2020

Giovanni Gerardo Muscolo Open the ORCID record for Giovanni Gerardo Muscolo [Opens in a new window] ,
Simone Marcheschi ,
Marco Fontana  and
Massimo Bergamasco
Giovanni Gerardo Muscolo*
Affiliation:
DIMEAS-Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129, Torino, Italy. E-mail: giovanni.muscolo@polito.it
Simone Marcheschi
Affiliation:
TeCIP Institute, Sant’Anna School of Advanced Studies, Via Alamanni 13B, San Giuliano Terme, Pisa, 56010, Italy. E-mails: simone.marcheschi@santannapisa.it; massimo.bergamasco@santannapisa.it
Marco Fontana
Affiliation:
Dipartimento di Ingegneria Industriale, University of Trento, Via Sommarive, 9, 38123 Povo, Trento, Italy. E-mail: marco.fontana-2@unitn.it
Massimo Bergamasco
Affiliation:
TeCIP Institute, Sant’Anna School of Advanced Studies, Via Alamanni 13B, San Giuliano Terme, Pisa, 56010, Italy. E-mails: simone.marcheschi@santannapisa.it; massimo.bergamasco@santannapisa.it
*
*Corresponding author. E-mail: giovanni.muscolo@polito.it
Get access Rights & Permissions [Opens in a new window]

Summary

This paper presents an experimental study on new paradigms of haptic-based teleoperated navigation of underwater vehicles. Specifically, the work is focused on investigating the possibility of enhancing the user interaction by introducing haptic cues at the level of the user wrist providing a force feedback that reflects dynamic forces on the remotely operated underwater vehicle. Different typologies of haptic controllers are conceived and integrated with a real-time simulated model of an underwater robotic vehicle. An experimental test is designed to evaluate the usability of the system and to provide information on the global performance during the execution of simple tasks. Experiments are conducted with 7 candidates testing 12 different controllers. Among these, the most effective strategies have been identified and selected on the basis of minimization of errors on the vehicle trajectory and of the quality of the user’s interaction in terms of perceived comfort during operation. Overall, the results obtained with this study underline that haptic navigation control can have a positive influence on the performance of remotely controlled underwater vehicles.

Keywords

Underwater teleoperationHaptic interfaceUnderwater vehicleHuman–machine control interfaceRobotics

Information

Type
Articles
Information
Robotica , Volume 39 , Issue 4 , April 2021 , pp. 618 - 632
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Sivev, S., Coleman, J., Omerdi, E., Dooly, G., Toal, D., “Underwater manipulators: A review,” Ocean Eng., 163, 431–450 (2018), ISSN 0029-8018, https://doi.org/10.1016/j.oceaneng.2018.06.018.CrossRefGoogle Scholar
Casalino, G., et al. “Underwater intervention robotics: An outline of the Italian National Project MARIS.” Marine Technol. Soc. J. 50(4), 98–107 (2016).CrossRefGoogle Scholar
WIMUST European Project, 12 February 2016, http://cordis.europa.eu/project/rcn/194287_en.html Google Scholar
Martin, S. C. and Whitcomb, L. L., “Fully actuated model-based control with six-degree-of-freedom coupled dynamical plant models for underwater vehicles: Theory and experimental evaluation,” Int. J. Robot. Res. 35(10), 1164–1184 (2016). doi: 10.1177/0278364915620032.CrossRefGoogle Scholar
12 February 2016 http://ec.europa.eu/maritimeaffairs/policy/blue_growth/index_en.htm Google Scholar
Iastrebov, V., Seet, G., Asokan, T., Chiu, Y. P., Lau, M. W. S., “Vision ehancement using stereoscopic telepresence for remotely operated underwater robotic vehicles,” J. Intell. Robot. Syst. 52, 139–154 (2008). doi: 10.1007/s10846-008-9203-z.CrossRefGoogle Scholar
Muscolo, G. G. and Cannata, G., “A Novel Tactile Sensor for Underwater Applications: Limits and Perspectives,” In: OCEANS 2015, Genova, 18-21 May (2015), pp. 1–7 doi: 10.1109/OCEANS-Genova.2015.7271717.CrossRefGoogle Scholar
Muscolo, G. G., Moretti, G. and Cannata, G., “SUAS: A novel soft underwater artificial skin with capacitive transducers and hyperelastic membrane,” Robotica 37(4), 756–777 (2019). doi: 10.1017/S0263574718001315.CrossRefGoogle Scholar
Aggarwal, A., Kampmann, P., Lemburg, J. and Kirchner, F., “Haptic object recognition in underwater and deep-sea environments,” J. Field Robot, 1–19 (2015), doi: 10.10027rob.21538.Google Scholar
Xu, P., et al., “Design of Control System and Human-Robot-Interaction System of Teleoperation Underwater Robot,” In: Intelligent Robotics and Applications (Springer International Publishing, 2019) pp., 649–660.CrossRefGoogle Scholar
Zhang, J., Liu, W., Gao, L., Li, L. and Li, Z., “The master adaptive impedance control and slave adaptive neural network control in underwater manipulator uncertainty teleoperation,” Ocean Eng. 165, 465–479 (2018), ISSN 0029-8018, https://doi.org/10.1016/j.oceaneng.2018.07.055.CrossRefGoogle Scholar
Kuiper, R. J., Frumau, J. C. L., van der Helm, F. C. T. and Abbink, D. A., “Haptic Support for Bi-Manual Control of a Suspended Grab for Deep-Sea Excavation,” In: IEEE International Conference on Systems, Man, and Cybernetics (2013).Google Scholar
Bowen, A. D., Yoerger, D. R., Taylor, C., McCabe, R., Howland, J., Gomez-Ibanez, D., Kinsey, J. C., Heintz, M., McDonald, G., Peters, D. B., Fletcher, B., Young, C., Buescher, J., Whitcomb, L. L., Martin, S. C., Webster, S. E. and Jakuba, M. V., “The Nereus Hybrid Underwater Robotic Vehicle for Global Ocean Science Operations to 11,000m Depth,” In: OCEANS 2008, 15–18 September (2008) pp. 1–10. doi: 10.1109/OCEANS.2008.5151993.Google Scholar
Liang, X., Li, Y., Peng, Z. and Zhang, J., “Nonlinear Dynamics Modeling and Performance Prediction for Underactuated AUV with Fins,” In: Nonlinear Dynamics (Springer Netherlands, 2015).Google Scholar
McLain, T. W. and Rock, S. M., “Development and experimental validation of an underwater manipulator hydrodynamic model,” Int. J. Robot. Res. 17, 748–759, 204 (1988).CrossRefGoogle Scholar
Gancet, J., et al., “DexROV: Enabling Effective Dexterous ROV Operations in Presence of Communication Latency,” In: OCEANS 2015, 18–21 May, Genova, Italy (2015).Google Scholar
Bogue, R., “Underwater robots: A review of technologies and applications,” Ind. Robot Int. J. 42 (3), 186–191 (2015).CrossRefGoogle Scholar
Ambar, R. B. and Sagara, S., “Development of a master controller for a 3-link dual-arm underwater robot,” Artif. Life Robot. 20, 327–335 (2015). doi: 10.1007/s10015-015-0234-9.CrossRefGoogle Scholar
Jamali, N., Kormushev, P., Vinas, A. C., Carreras, M. and Caldwell, D. G., “Underwater Robot-Object Contact Perception Using Machine Learning on Force/Torque Sensor Feedback,” In: IEEE International Conference on Robotics and Automation (ICRA). Washington State Convention Center. Seattle, Washington, May 26–30 (2015).Google Scholar
Rydén, F., Stewart, A. and Chizeck, H. J., “Advanced Telerobotic Underwater Manipulation Using Virtual Fixtures and Haptic Rendering,” In: OCEANS MTS 2013 (2013).Google Scholar
Slotine, J. J. E. and Li, W., Applied Nonlinear Control (Prentice Hall, New York, 1991).Google Scholar
Ha, C. S., Park, S., Her, J., Jang, I., Lee, Y., Cho, G. R., Son, H. I and Lee, D., “Whole-Body Multi-Modal Semi-Autonomous Teleoperation of Mobile Manipulator Systems,” In: IEEE International Conference on Robotics and Automation (ICRA). Washington State Convention Center. Seattle, Washington, May 26–30 (2015).Google Scholar
Di Lillo, P., Di Vito, D., Simetti, E., Casalino, G. and Antonelli, G., “Satellite-Based Tele-Operation of an Underwater Vehicle-Manipulator System. Preliminary Experimental Results,” In: 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, (2018) pp. 7504–7509. doi: 10.1109/ICRA.2018.8462976 CrossRefGoogle Scholar
Diolaiti, N. and Melchiorri, C., “Haptic tele-operation of a mobile robot,” IFAC Proc. Vol. 36(17), 521–526 (2003).CrossRefGoogle Scholar
Le, K. D., Nguyen, H. D., Ranthumugala, D. and Forrets, A., “Haptic Driving System for Surge Motion Control of Underwater Remotely Operated Vehicles,” Proceedings of 2014 International Conference on Modelling, Identification and Control, Melbourne, Australia, December 3–5 (2014).CrossRefGoogle Scholar
Rosati Papini, G. P., Fontana, M. and Bergamasco, M., “Desktop haptic interface for simulation of hand-tremor,”IEEE Trans. Haptics 9(1) (2016).CrossRefGoogle Scholar
Antonelli, G., Underwater Robots. Motion and Force Control of Vehicle-Manipulator Systems. Springer Tracts in Advanced Robotics (Springer-Verlag, Heidelberg, Germany, 2003).Google Scholar
Antonelli, G., Chiaverini, S., Sarkar, N. and West, M., “Adaptive control of an autonomous underwater vehicle: Experimental results on ODIN,” IEEE Trans. Cont. Syst. Technol. 9(5) (2001).Google Scholar
Choi, S. K., Takashige, G. Y. and Yuh, J., “Experimental Study on an Underwater Robotic Vehicle: ODIN,” Proceedings of the 1994 Symposium on Autonomous Underwater Vehicle Technology, AUV 1994. 19–20 July (1994) pp. 79–84. doi: 10.1109/AUV.1994.518610.CrossRefGoogle Scholar
Choi, H. T., Hanai, A., Choi, S. K. and Yuh, J., “Development of an underwater robot, ODIN-III,” Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), vol. 1, 27–31 October (2003) pp. 836–841. doi: 10.1109/IROS.2003.1250733 CrossRefGoogle Scholar
Do, K. D., et al., “A global output-feedback controller for stabilization and tracking of underactuated ODIN: A spherical underwater vehicle,” Automatica 40, 117–124 (2004).CrossRefGoogle Scholar
Fossen, T. I., Guidance and Control of Ocean Vehicles (John Wiley and Sons, Chichester, UK, 1994).Google Scholar
Fossen, T. I., Marine Control Systems: Guidance, Navigation and Control of Ships, Rigs and Underwater Vehicles (Marine Cybernetics AS, Trondheim, Norway, 2002).Google Scholar
Yuh, J., “Development in Underwater Robotics,” In: IEEE International Conference on Robotics and Automation, Nagoya, Japan (1995) pp. 1862–1867.Google Scholar
Yuh, J., “Exploring the Mysterious Underwater World with Robots,” In: 6th IFAC Conference on Manoeuvring and Control of Marine Craft, Girona, Spain (2003).Google Scholar
Yuh, J. and West, M. (2001). “Underwater robotics,” J. Adv. Robot. 15, 609–639.CrossRefGoogle Scholar
Ura, T., “Steps to Intelligent AUVs,” In: 6th IFAC Conference on Manoeuvring and Control of Marine Craft, Girona, Spain (2003).Google Scholar
SNAME. The Society of Naval Architects and Marine Engineers, “Nomenclature for Treating the Motion of a Submerged Body Through a Fluid,” In: Technical and Research Bulletin (1950) pp. 1–5.Google Scholar
Leabourne, K. N., Rock, S. M. and Lee, M. J., “Model Development of an Underwater Manipulator for Coordinated Arm-Vehicle Control,” In: MTS/IEEE Techno-Ocean 1998, Nice, France (1998) pp. 941–994.Google Scholar
Fjellstad, O. and Fossen, T. I., “Position and attitude tracking of AUVs: A quaternion feedback approach,” IEEE J. Oceanic Eng. 19, 512–518 (1994).CrossRefGoogle Scholar
Yuh, J., Nie, J. and Lee, C. S. G., “Experimental Study on Adaptive Control of Underwater Robots,” In: IEEE International Conference on Robotics and Automation, Detroit, Michigan (1999) pp. 393–398 Google Scholar
O. Fjellstad and T. I. Fossen Singularity-Free Tracking of Unmanned Underwater Vehicles in 6DOF. In: 1994 IEEE Conference on Decision and Control, Lake Buena Vista, Florida (1994) pp. 1128–1133 Google Scholar
Fossen, T. I and Balchen, J., “The NEROV Autonomous Underwater Vehicle,” In: MTS/IEEE Techno-Ocean 1991 Conference, Honolulu, Hawaii (1991).Google Scholar
Antonelli, G., et al., “A Novel Adaptive Control Law for Autonomous Underwater Vehicles,” In: IEEE International Conference on Robotics and Automation, ICRA 2001, vol. 1 (2001) pp. 447–452.Google Scholar
Sun, Y. C. and Cheah, C. C., “Adaptive Set point Control for Autonomous Underwater Vehicles,” In: 2003 IEEE Conference on Decision and Control, Maui, Hawaii (2003) pp. 1262–1267.Google Scholar