Skip to main content

Virtual Reality and Autonomous Systems to Enhance Underwater Situational and Spatial Awareness

  • Conference paper
  • First Online:
Modelling and Simulation for Autonomous Systems (MESAS 2019)

Abstract

This paper presents a virtual/augmented reality (VR/AR) framework to enhance the situational and spatial awareness at tactical level in the underwater domain. Technology supporting operations in this challenging environment has been scarcely explored in the literature. Consequently, a detailed study has been carried out in order to identify all the steps necessary to transform underwater data into formats suitable for the representation in VR/AR environments. In this context, an application for enhancing the situational and, more precisely, the spatial awareness in the maritime domain has been drafted and proposed.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

Similar content being viewed by others

References

  1. Riley, J., Endsley, M., Bolstad, C., Cuevas, H.: Collaborative planning and situation awareness in army command and control. Ergonomics 49(12–13), 1139–1153 (2006)

    Article  Google Scholar 

  2. Papasin, R., et al.: Intelligent virtual station. In: 7th International Symposium (2003)

    Google Scholar 

  3. Zocco, A., De Paolis, L.: Augmented command and control table to support network-centric operations. Def. Sci. J. 65(1), 39 (2015)

    Article  Google Scholar 

  4. NATO C2 Centre for Excellence: MCDC 2017-18 - Information Age Command and Control Concepts. https://wss.apan.org/s/MCDCpub/MCDC1718/MCDC_201718_Public_Shared_Documents/MCDC_17-18_Project_Fact_Sheets/MCDC_17-18_InfoAgeC2_Project.pdf. Accessed 24 Jan 2018

  5. VR Scout: The Australian Air Force is Now Testing the Microsoft HoloLens. https://vrscout.com/news/the-australian-air-force-is-now-testing-the-microsoft-hololens. Accessed 23 Jan 2017

  6. Františ, P., Hodický, J.: Virtual reality in presentation layer of C3I system. In: MODSIM05 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings, pp. 3045–3050 (2005)

    Google Scholar 

  7. Fleischer, S., Rock, S., Lee, M.: Underwater vehicle control from a virtual environment interface. In: Symposium on Interactive 3D Graphics, Monterey, CA, USA, April 1995

    Google Scholar 

  8. Piguet, L., Hine, B., Hontalas, P., Fong, T., Nygren, E.: The virtual environment vehicle interface: a dynamic, distributed and flexible virtual environment. In: IMAGINA 1996: New Frontiers of CyberExistence (1996)

    Google Scholar 

  9. Stoll, E., Wilde, M., Pong, C.: Using virtual reality for human-assisted in-space robotic assembly. In: World Congress on Engineering and Computer Science (2009)

    Google Scholar 

  10. Bualat, M.: Astrobee Space Station Robotic Free Flyer. NASA. https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20160009763.pdf. Accessed 28 July 2016

  11. Lin, Q., Kuo, C.: Assisting the teleoperation of an unmanned underwater vehicle using a synthetic subsea scenario. Presence 8(5), 520–530 (1999)

    Article  Google Scholar 

  12. US DoD: Eyes in the Dark: Navy Dive Helmet Display Emerges as Game-Changer. https://www.defense.gov/News/Article/Article/873877/eyes-in-the-dark-navy-dive-helmet-display-emerges-as-game-changer/. Accessed 27 July 2016

  13. Morales, R., Keitler, P., Maier, P., Klinker, G.: An underwater augmented reality system for commercial diving operations. In: OCEANS, Biloxi, MS, USA. IEEE (2009)

    Google Scholar 

  14. LSTS: NEPTUS Command and Control Software. https://lsts.fe.up.pt/toolchain/neptus

  15. SeeByte: SeaTrack V4. http://www.seebyte.com/military/seetrack-military/

  16. Louvieris, P., Collins, C., Mashanovich, N.: Investigating the use and effectiveness of virtual collaboration desks for collaborative military planning. In: 42nd Hawaii International Conference on System Sciences, HICSS 2009 (2009)

    Google Scholar 

  17. Duklis, P.: The Joint Reserve Component Virtual Information Operations organization (JRVIO); Cyber Warriors Just a Click Away, Carlisle Barracks, PA, U.S. (2006)

    Google Scholar 

  18. Carvalho, M., Ford, R.: NextVC2—a next generation virtual world command and control. In: Military Communications Conference, MIILCOM, pp. 1–6 (2012)

    Google Scholar 

  19. Roldan, J., Peña-Tapia, E., Martín-Barrio, A., Olivares-Méndez, M., Del Cerro, J., Barrientos, A.: Multi-robot interfaces and operator situational awareness: study of the impact of immersion and prediction. Sensors 17(8), 1720 (2017)

    Article  Google Scholar 

  20. Smallman, H.S., Rieth, C.A.: ADVICE: decision support for complex geospatial decision making tasks. In: Lackey, S., Chen, J. (eds.) VAMR 2017. LNCS, vol. 10280, pp. 453–465. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-57987-0_37

    Chapter  Google Scholar 

  21. Hou, M., Kobierski, R., Herdman, C.: Design and evaluation of intelligent adaptive operator interfaces for the control of multiple UAVs. In: NATO RTO HFM 135 Symposium, Biarizze, France (2006)

    Google Scholar 

  22. Machine Learning & Recommender Systems for C2 of Autonomous Vehicles. https://www.dst.defence.gov.au/sites/default/files/events/documents/ISTAS-2016_Machine_Learning_Recommender_Systems_Glenn-Moy.pdf

  23. Františ, P., Hodický, J.: Virtual reality in presentation layer of C3I system. In: MODSIM05 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Melbourne, Australia, pp. 3045–3050 (2005)

    Google Scholar 

  24. Urick, R.: Principles of Underwater Sound, 3rd edn. Peninsula Publishing, Newport Beach (2013)

    Google Scholar 

  25. Hurtós, N.: Forward-looking sonar mosaicing for underwater environments. Universitat de Girona, Girona, Spain (2014)

    Google Scholar 

  26. https://noaacoastsurvey.wordpress.com/tag/side-scan-sonar/

  27. https://www.idaholidar.org/blog/2015/04/14/nsf-grant-to-develop-lidar-tools/

  28. Coiras, E., Groen, J.: 3D target shape from SAS images based on a deformable mesh. In: Proceedings of the 3rd International Conference and Exhibition on Underwater Acoustic Measurements: Technologies and Result, Nafplion, Greece (2009)

    Google Scholar 

  29. Guerneve, T., Petillot, Y.: Underwater 3D reconstruction using BlueView imaging sonar. In: IEEE Oceans, Genova, Italy (2005)

    Google Scholar 

  30. Trucco, A., Curletto, S.: Extraction of 3D information from sonar image sequences. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 33(4), 687–699 (2003)

    Article  Google Scholar 

  31. Kulawiak, M., Lubniewski, Z.: 3D imaging of underwater objects using multi-beam data. Hydroacustic 17, 123–128 (2014)

    Google Scholar 

  32. Machado, D., Furfaro, T., Dugelay, S.: Micro-bathymetry data acquisition for 3D reconstruction of objects on the sea floor. In: OCEANS 2017, Aberdeen, UK (2017)

    Google Scholar 

  33. Hoppe, H., DeRose, T., Duchamp, T., McDonald, J.: Surface reconstruction from unorganized points. In: Proceedings of the 19th Annual Conference on Computer Graphics and Interactive Techniques, New York, NW, USA (1992)

    Google Scholar 

  34. Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Fourth Eurographics Symposium on Geometry Processing, Aire-la-Ville, Switzerland (2006)

    Google Scholar 

  35. Amenta, N., Choi, S., Dey, T.K., Leekha, N.: A simple algorithm for homeomorphic surface reconstruction. In: Proceedings of the Sixteenth Annual Symposium on Computational Geometry, New York, NY, USA (2000)

    Google Scholar 

  36. Cohen-Steiner, D., Da, F.: A Greed Delaunay-based surface reconstruction algorithm. Visual Comput. Int. J. Comput. Graphics 20(1), 4–16 (2004). https://doi.org/10.1007/s00371-003-0217-z

    Article  Google Scholar 

  37. https://github.com/domlysz/BlenderGIS/wiki/Make-terrain-mesh-with-Delaunay-triangulation

Download references

Acknowledgements

The researches described in this paper have been funded by Allied Command Transformation in the PARC project and by the NATO Head Quarter Defence Against Terrorism Programme of Work (DAT POW).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alberto Tremori .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 NATO

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tremori, A., Carrera Viñas, A., Solarna, D., Caamaño Sobrino, P., Godfrey, S.B. (2020). Virtual Reality and Autonomous Systems to Enhance Underwater Situational and Spatial Awareness. In: Mazal, J., Fagiolini, A., Vasik, P. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2019. Lecture Notes in Computer Science(), vol 11995. Springer, Cham. https://doi.org/10.1007/978-3-030-43890-6_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-43890-6_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43889-0

  • Online ISBN: 978-3-030-43890-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics