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Dynamic modeling of an autonomous underwater vehicle

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Abstract

The EcoMapper is an autonomous underwater vehicle that has broad applications, such as water quality monitoring and bathymetric survey. To simulate its dynamics and to precisely control it, a dynamic model is needed. In this paper, we develop a mathematical model of the EcoMapper based on computational-fluid-dynamics calculations, strip theory, and open-water tests. We validate the proposed model with the results of the field experiments carried out in the west pond in the Georgia Tech Savannah Campus.

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References

  1. Ellison R, Slocum D (2008) High spatial resolution mapping of water quality and bathymetry with a person-deployable, low cost autonomous underwater vehicle. OCEANS 2008:1–7

    Google Scholar 

  2. Hollinger G, Mitra U, Sukhatme G (2012) Active and adaptive dive planning for dense bathymetric mapping. In: Proceedings of the international conference on experimental robotics (ISER), pp 1–7

  3. Mukhopadhyay S, Wang C, Bradshaw S, Maxon S, Patterson M, Zhang F (2012) Controller performance of marine robots in reminiscent oil surveys. In: Proceeding of the 2012 IEEE/RSJ international conference on intelligent robots and systems (IROS 2012), pp 1766–1771

  4. Murphy R, Steimle E, Hall M, Lindemuth M, Trejo D, Hurlebaus S, Medina-Cetina Z, Slocum D (2009) Robot-assisted bridge inspection after hurricane IKE. In: 2009 IEEE international workshop on safety, security rescue robotics (SSRR), pp 1–5

  5. DeArruda J (2010) Oceanserver IVER2 autonomous underwater vehicle remote Helm functionality. OCEANS 2010:1–5

    Google Scholar 

  6. Antonelli G (2006) Underwater robots-motion and force control of vehicle-manipulator systems. Springer-Verlag, Berlin

    Google Scholar 

  7. Fossen TI (1994) Gaudiance and control of ocean vehicles. Wiley, Chichester

    Google Scholar 

  8. de Barros E, Dantas J, Pascoal A, de Sa E (2008) Investigation of normal force and moment coefficients for an AUV at nonlinear angle of attack and sideslip range. IEEE J Oceanic Eng 33:538–549

    Article  Google Scholar 

  9. Hwang YL (2003) Hydrodynamic modeling of LMRS unmanned underwater vehicle and tow tank test validation. OCEANS 2003:1425–1430

    Google Scholar 

  10. Williams C, Curtis T, Doucet J, Issac M, Azarsina F (2006) Effects of hull length on the hydrodynamic loads on a slender underwater vehicle during manoeuvres. OCEANS 2006:1–6

    Google Scholar 

  11. Prestero T (2001) Verification of a six-degree of freedom simulation model for the REMUS autonomous underwater vehicle. Master’s thesis, Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, MA, USA

  12. Von Alt C, Grassle J (1992) Leo-15 an unmanned long term environmental observatory. OCEANS 1992(2):849–854

    Google Scholar 

  13. Boger DA, Dreyer JJ (2006) Prediction of hydrodynamic forces and moments for underwater vehicles using overset grids. In: Proceeding of 44th AIAA aerospace sciences meeting and exhibit, pp 1–13

  14. Chin C, Lau M (2012) Modeling and testing of hydrodynamic damping model for a complex-shaped remotely-operated vehicle for control. J Mar Sci Appl 11:150–163

    Article  Google Scholar 

  15. Jagadeesh P, Murali K (2006) Investigation of alternative turbulence closure models for axis symmetric underwater hull forms. J Ocean Technol 1:37–57

    Google Scholar 

  16. Mulvany N, Tu JY, Chen L, Anderson B (2004) Assessment of two-equation turbulence modeling for high Reynolds number hydrofoil flow. Int J Numer Methods Fluids 45:275–299

    Article  MATH  Google Scholar 

  17. Racine BJ, Paterson EG (2005) CFD-based method for simulation of marine-vehicle maneuvering. In: Proceeding of 35th AIAA fluid dynamics conference and exhibit, pp 1–22

  18. Tang S, Ura T, Nakatani T, Thornton B, Jiang T (2009) Estimation of the hydrodynamic coefficients of the complex-shaped autonomous underwater vehicle tuna-sand. J Marine Sci Technol 14:373–386

    Article  Google Scholar 

  19. Nakatani T, Ura T, Ito Y, Kojima J, Tamura K, Sakamaki T, Nose Y (2008) AUV “TUNA-SAND” and its exploration of hydrothermal vents at Kagoshima Bay. In: OCEANS 2008, MTS/IEEE Kobe Techno-Ocean, pp 1–5

  20. Perez T (2010) Ship motion control: course keeping and roll stabilisation using rudder and fins. Springer, New York

  21. DeMarco K, West M, Collins T (2011) An implementation of ROS on the yellowfin autonomous underwater vehicle (AUV). OCEANS 2011:1–7

    Google Scholar 

  22. Melim A, West M (2011) Towards autonomous navigation with the yellowfin AUV. OCEANS 2011:1–5

    Google Scholar 

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Correspondence to Chuanfeng Wang.

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Wang, C., Zhang, F. & Schaefer, D. Dynamic modeling of an autonomous underwater vehicle. J Mar Sci Technol 20, 199–212 (2015). https://doi.org/10.1007/s00773-014-0259-0

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  • DOI: https://doi.org/10.1007/s00773-014-0259-0

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