Skip to main content
SpringerLink
Log in
Book cover

Workshop of Physical Agents

WAF 2020: Advances in Physical Agents II pp 227–240Cite as

Open-Loop Sidescan Sonar Mosaic and ANN Velocity Estimation

  • Conference paper
  • First Online:

  • 631 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1285))

Abstract

This paper presents a system to generate open-loop mosaics from the images obtained by a sidescan sonar using dead reckoning as a positioning system in a low cost ROV, which does not include a Doppler velocity log (DVL). The ROV velocity is then estimated using an artificial neural network (ANN) for feeding the dead reckoning positioning. The training process of the neural network is also described. The sidescan sonar readings are used, based on the currently estimated position, to update the sonar mosaic. The process of the transformations and corrections of the sidescan sonar are also described. Finally, some results obtained in a thermal power plant are presented.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. León Martín, J.D.: Del Escandallo a los Sondadores Multihaz. Escuela de Hidrografía, Armada Española (2004)

    Google Scholar 

  2. Zitová, B., Flusser, J.: Image registration methods. In: Todorovic S. (ed.) Image and Vision Computing, pp. 977–1000 (2003). https://doi.org/10.1016/S0262-8856(03)00137-9

  3. Bennell, J.D.: Mosaicing of sidescan sonar images to map seabed features. In: Davies, J. (ed.) Marine Monitoring Handbook, pp. 1–5 (2001)

    Google Scholar 

  4. Blondel, P.: The Handbook of Sidescan Sonar (2009)

    Google Scholar 

  5. Palomer, A., Ridao, P., Ribas, D.: Multibeam 3D underwater SLAM with probabilistic registration. Sensors 16, 560 (2016). https://doi.org/10.3390/s16040560

  6. Rahman, S., Quattrini Li, A., Rekleitis, I.: Sonar visual inertial SLAM of underwater structures. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1–7 (2018). https://doi.org/10.1109/ICRA.2018.8460545

  7. Zhao, J., Yan, J., Zhang, Z., Meng, J.: A new radiometric correction method for side-scan sonar images in consideration of seabed sediment variation. Remote Sens. 9(6), 575 (2017). https://doi.org/10.3390/rs9060575

    Article  Google Scholar 

  8. Barron, J.L., Beauchemin, S.S.: The computation of optical flow. ACM Comput. Surv. 35 (1995). https://doi.org/10.1145/212094.212141

  9. Chailloux, C., Zerr, B.: Non symbolic methods to register sonar images. Oceans 276–281 (2005). https://doi.org/10.1109/OCEANSE.2005.1511725

  10. Vandrish, P., Vardy, A., Walker, D., Dobre, A.O.: Side-scan sonar image registration for AUV navigation. In: Underwater Technology (UT), 2011 IEEE Symposium on and 2011 Workshop on Scientific Use of Submarine Cables and Related Technologies (SSC), pp. 1–7. IEEE Xplore (2011). https://doi.org/10.1109/UT.2011.5774096

  11. Zhao, J., Wang, A., Zhang, H., Wang, X.: Mosaic method of side-scan sonar strip images using corresponding features. IET Image Process 616–623 (2013). https://doi.org/10.1049/iet-ipr.2012.0468

  12. Chailloux, C., Le Caillec, J.M., Gueriot, D., Zerr, B.: Intensity-based block matching algorithm for mosaicing sonar images. IEEE J. Oceanic Eng. 36(4), 627–645. https://doi.org/10.1109/JOE.2011.2141850

  13. Fotouhi, A., Montazeri, M., Jannatipour, M.: Vehicle’s velocity time series prediction using neural network. Systems Simulation and Control Laboratory, Iran (2011)

    Google Scholar 

  14. Thorsell, E.: Vehicle speed-profile prediction without spatial information. Chalmers University of Technology, Sweden (2013)

    Google Scholar 

  15. Karras, G.C., Kyriakopoulos, K.J.: Localization of an underwater vehicle using an IMU and a laser-based vision system. In: Mediterranean Conference on Control Automation, Athens, pp. 1–6 (2007). https://doi.org/10.1109/MED.2007.4433777

  16. Zhao, B., Blanke, M., Skjetne, R.: Particle filter ROV navigation using hydroacoustic position and speed log measurements. In: American Control Conference (ACC), Montreal, pp. 6209–6215 (2012). https://doi.org/10.1109/ACC.2012.6315511

  17. Ye, X., Yang, H., Li, C., Jia, Y., Li, P.: A gray scale correction method for side-scan sonar images based on Retinex. Remote Sens. (2019). https://doi.org/10.3390/rs11111281

    Article  Google Scholar 

  18. Burguera, A., Oliver, G.: High-resolution underwater mapping using side-scan sonar. PLOS One 1–41 (2016). https://doi.org/10.1371/journal.pone.0146396

  19. Gautier, S., Morissette, G.: Unsupervised extraction of underwater regions of interest in sidescan sonar imagery. J. Ocean Technol. 15, 1–15 (2019)

    Google Scholar 

  20. Wu, X.: An efficient antialiasing technique. In: ACM SIGGRAPH Computer Graphics, pp. 143–152 (1991). https://doi.org/10.1145/127719.122734

Download references

Author information

Authors and Affiliations

  1. Department of Information and Communication Engineering, University of Murcia, 30100, Murcia, Spain

    José Manuel Bernabé Murcia & Humberto Martínez-Barberá

Authors
  1. José Manuel Bernabé Murcia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Humberto Martínez-Barberá
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to José Manuel Bernabé Murcia .

Editor information

Editors and Affiliations

  1. Electronics Department, University of Alcalá, Madrid, Spain

    Luis M. Bergasa

  2. Electronics Department, University of Alcalá, Madrid, Spain

    Manuel Ocaña

  3. Electronics Department, University of Alcalá, Madrid, Spain

    Rafael Barea

  4. Electronics Department, University of Alcalá, Madrid, Spain

    Elena López-Guillén

  5. Electronics Department, University of Alcalá, Madrid, Spain

    Pedro Revenga

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bernabé Murcia, J.M., Martínez-Barberá, H. (2021). Open-Loop Sidescan Sonar Mosaic and ANN Velocity Estimation. In: Bergasa, L.M., Ocaña, M., Barea, R., López-Guillén, E., Revenga, P. (eds) Advances in Physical Agents II. WAF 2020. Advances in Intelligent Systems and Computing, vol 1285. Springer, Cham. https://doi.org/10.1007/978-3-030-62579-5_16

Download citation

Publish with us

Policies and ethics

Search

Navigation