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Autonomous control of the underwater remotely operated vehicle in collision situation with stationary obstacle

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article considers the problem of autonomous control of the underwater remotely operated vehicle mini Remotely Operated Vehicle (ROV) in a collision situation with a stationary obstacle. The control of the collision avoidance process is presented as a synthesis of fuzzy proportional-differential controllers for the control of distance and orientation concerning the detected stationary obstacle. The control of the submergence depth of the underwater vehicle has been adopted as a separate control flow. A method to obtain the main motion parameters of the underwater vehicle relative to the detected stationary obstacle using a Laser-based Vision System (LVS) and a pressure sensor coupled to an Inertial Measurement Unit (IMU) is described and discussed. The result of computer implementation of the designed fuzzy controllers for collision avoidance is demonstrated in simulation tests and experiments carried out with the mini ROV in the test pool.
Rocznik
Tom
Strony
45--55
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
  • Gdansk University of Technology Poland
  • Mode S.A. Poland
Bibliografia
  • 1. Rowiński L. Submersible vehicles construction and equipment, Private enterprise “WiB” Gdańsk, 2008 (in Polish).
  • 2. Sahoo A., Dwivedy S. K., Robi P.S., Advancements in the field of autonomous underwater vehicle, Ocean Engineering, Vol. 181, 2019, pp. 145-160.
  • 3. Kinsey, J. C., Eustice, R. M., & Whitcomb, L. L., A survey of underwater vehicle navigation: Recent advances and new challenges, In IFAC Conference of Manoeuvering and Control of Marine Craft vol. 88, 2006, pp. 1-12.
  • 4. Jurczyk K., Piskur P., Szymak P., Parameters identification of the flexible fin kinematics model using vision and genetic algorithms, Polish Maritime Research, 27(2), 2020, pp. 39–47, https://doi.org/10.2478/pomr-2020-0025.
  • 5. Żak A. Simulation model of an unmanned underwater robot, Scientific Journals of the Naval Academy, No 3 (158), Gdynia, 2004, pp. 135-150 (in Polish).
  • 6. Kostas G., Kyriakopoulos K., Localization of an Underwater Vehicle using an IMU and a Laser-based Vision System, Proceedings of the 15th Mediterranean Conference on Control & Automation, July 27–29, Athens – Greece, 2007.
  • 7. Lamraoui, Habib Choukri and Qidan, Zhu, Path Following Control of Fully Actuated Autonomous Underwater Vehicle Based on LADR, Polish Maritime Research, vol. 25, no. 4, 2018, pp.39-48. https://doi.org/10.2478/pomr-2018-0130.
  • 8. Garus J., Szymak P., Fuzzy control of the course and submergence of a submarine vehicle - simulation and experimental studies, Scientific Journals of the Naval Academy, No 2 (157), Gdynia, 2004, pp. 47-56 (in Polish).
  • 9. Michalski, Jan, Parametric method for determination of motion characteristics of underwater vehicles, applicable in preliminary designing, Polish Maritime Research, vol. 16, no. 2, 2009, pp.3-10, doi: 10.2478/v10012-008-0016-6.
  • 10. Fossen, T. I., Guidance and Control of Ocean Vehicles. Chichester: John Wiley & Sons Ltd, 1994.
  • 11. Fossen, T. I., Marine Control Systems: Guidance, Navigation and Control of Ships, Rigs and Underwater Vehicles. Trondheim: Marine Cybernetics AS, 2002.
  • 12. Fossen, T. I., Handbook of Marine Craft Hydrodynamics and Motion Control. Chichester: John Wiley and Sons Ltd, 2011.
  • 13. Żak A., Fuzzy controller for underwater remotely operated vehicle which moving in conditions of environment disturbance occurrence, Journal of KONES Powertrain and Transport, Vol. 18, No. 2, , 2011, pp. 499-507.
  • 14. David K. K., Vicerra R., Bandala A., Gan Lim L., Dadios E., Unmanned Underwater Vehicle Navigation and Collision Avoidance Using Fuzzy Logic, Proceedings of the 2013 IEEE/ SICE International Symposium on System Integration, Kobe International Conference Center, Kobe, Japan, December 15-17, 2013, pp. 126-131.
  • 15. Śmierzchalski R., Ship automation and control, Gdansk University of Technology Publishing, Gdańsk, 2013 (in Polish).
  • 16. Miskovic N., Vukic Z., Petrovic I., Distance Keeping for Underwater Vehicles – Tuning Kalman Filters Using Self-Oscillation, Proceedings of the IEEE OCEANS’09 Conference Bremen, 2009.
  • 17. OpenROV Underwater Drone (2015), http://www.openrov. com, December 08. 2015.
  • 18. Malina W., Smiatacz M., Methods of digital image processing, Academic Publishing House EXIT, Warszawa, 2005 (in Polish).
  • 19. Mallick S., Blob Detection Using OpenCV (Python, C++), https://www.learnopencv.com/blob-detection-using-opencv-python-c/, February 17, 2015.
  • 20. Malec M., Morawski M., Szymak P., Concept for the development of CyberRyba, Polish Society of Hyperbaric Medicine and Technology, Gdynia, 2010 (in Polish).
  • 21. Piskur, Pawel, Szymak, Piotr, Kitowski, Zygmunt and Flis, Leszek., Influence of Fin’s Material Capabilities on the Propulsion System of Biomimetic Underwater Vehicle, Polish Maritime Research, vol. 27, no. 4, 2020, pp. 179-185, doi: 10.2478/pomr-2020-0078.
  • 22. Piegat A., Fuzzy modeling and control, Academic Publishing House EXIT, Warszawa 2003.
  • 23. SciKit-Fuzzy Python, http://pythonhosted.org/scikit-fuzzy/ overview.html, February 16, 2021.
  • 24. P. J. B. Sanchez et al., “Use of UIoT for Offshore Surveys through Autonomous Vehicles” Polish Maritime Research, vol. 28, no. 3. 2021, doi: 10.2478/pomr-2021-0044.
  • 25. M. A. Salim, A. Noordin, A. N. Jahari, A Robust of Fuzzy Logic and Proportional Derivative Control System for Monitoring Underwater Vehicles, 2010 Second International Conference on Computer Research and Development, Kuala Lumpur, 2010, pp. 849–853.
  • 26. L. Song et al., “Method of Emergency Collision Avoidance for Unmanned Surface Vehicle (USV) Based on Motion Ability Database,” Polish Maritime Research, vol. 26, no. 2, 2019, doi: 10.2478/pomr-2019-0025.
  • 27. S. Ni, Z. Liu, Y. Cai, and X. Wang, “Modelling of Ship’s Trajectory Planning in Collision Situations by Hybrid Genetic Algorithm,” Polish Maritime Research, vol. 25, no. 3, 2018, doi: 10.2478/pomr-2018-0092.
  • 28. J. Zhuang, L. Zhang, Z. Qin, H. Sun, B. Wang, and J. Cao, “Motion Control and Collision Avoidance Algorithms for Unmanned Surface Vehicle Swarm in Practical Maritime Environment,” Polish Maritime Research, vol. 26, no. 1, 2019, doi: 10.2478/pomr-2019-0012.
  • 29. Z. Dong, S Qi, M Yu, Z Zhang, H Zhang, J Li, and Y Liu., “An Improved Dynamic Surface Sliding Mode Method for Autonomous Cooperative Formation Control of Underactuated USVS with Complex Marine Environment Disturbances,” Polish Maritime Research, vol. 29, no. 3, 2022, pp. 47-60, doi: 10.2478/pomr-2022-0025.
  • 30. M. Kapczyński, “Collision avoidance by operated controlled underwater vehicle with stationary objects”, Gdansk University of Technology, Gdańsk, 2016 (in Polish).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3037853b-8428-4e3b-9d64-1fbde707702c
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