Autonomous Underwater Vehicles

Autonomous Underwater Vehicles (AUVs) or Unmanned Autonomous Underwater Vehicles (UAUVs) are self-propelled robots that belong to a family of instruments known as Unmanned Underwater Vehicles (UUVs), which includes Remotely Operated Vehicles (ROVs). Unlike ROVs, AUVs are not connected (or ‘tethered’) to a mother vessel, and do not require direct human control during data collection, having therefore a greater mobility, space, range and/or speed. They can be used in remote and hostile parts of the ocean hitherto inaccessible by vessels, such as under ice in Polar Regions or deep water hydrothermal vents (Graham et al., 2013).

© http://auvac.org/. The Memorial University (MUN) Explorer AUV is the ‘flagship’ vehicle in the lab, used currently for environmental monitoring, seabed imaging, and vehicle dynamics testing. See more at http://auvac.org/configurations/view/207#sthash.693diL5y.dpuf

© http://auvac.org/. The Memorial University (MUN) Explorer AUV is the ‘flagship’ vehicle in the lab, used currently for environmental monitoring, seabed imaging, and vehicle dynamics testing. See more at http://auvac.org

AUV Applications

Thanks to advancing technology, Autonomous Underwater Vehicle usage is pushing boundaries, and has expanded from military and security purposes to entertainment as a hobby. Commercially, Autonomous Underwater Vehicles are used by Oil & Gas (O&G) companies to map the seafloor prior to installation/construction of ocean structures, such as rigs, platforms, or pipelines (Blidberg, 2010). Within the research environment, Autonomous Underwater Vehicles are used also for seafloor mapping and oceanographic measurement applications. For example, AUVs are used for studies of chemosynthetic communities in hydrothermal ecosystems, where emitted fluids can be over 400 °C (German et al., 2008, Nakamura et al., 2013) (http://en.wikipedia.org), or abyssal zone imaging of sea floor biodiversity (Nakazawa, Ushio & Kondoh, 2011). Their usage in research projects is reflected in elevated numbers of peer-reviewed marine publications, which rapidly increased in the last ten years (Wynn et al., 2014).

An AUV’s ability to sense its surroundings is termed ‘situational awareness’. Image courtesy of AUVfest 2008: Partnership Runs Deep, Navy/NOAA ©http://oceanexplorer.noaa.gov/.

An AUV’s ability to sense its surroundings is termed ‘situational awareness’. Image courtesy of AUVfest 2008: Partnership Runs Deep, Navy/NOAA ©http://oceanexplorer.noaa.gov/.

Autonomous Underwater Vehicles are now also being used during Passive Acoustic Monitoring (PAM) for marine mammal research (see www.passiveacousticmonitoring.com for definitions of PAM) and mitigation during offshore industrial activities (http://www.marinemammalmitigationplan.co.uk/). Baumgartner et al., (2013), used two underwater electric gliders (http://www.webbresearch.com) to detect acoustically the calls of fin whales (Balaenoptera physalus), humpback whales (Megaptera novaeangliae), sei whales (Balaenoptera borealis), and North Atlantic right whales (Eubalaena glacialis) in the Gulf of Maine. To assess the accuracy of gliders detection using PAM, a visual ground-truthing aerial survey was conducted. From the ten cases that whales were detected visually, nine were also detected acoustically in real time.

Wave gliders

Wave gliders (http://liquidr.com) also have potential to support Passive Acoustic Monitoring studies. Design resembles a surfboard and the glider is essentially an ocean surface drone with an array of sensors including hydrophones for PAM, current profilers (http://en.wikipedia.org), sonar for bathymetry measurements, and cameras for imaging. In addition to its autonomy, the glider is powered by solar and wave power and hence, aside from during the manufacturing process, has a low carbon footprint.

A liquid robotics wave glider. View this vide to see how it works: http://liquidr.com/technology/waveglider/how-it-works.html

A liquid robotics wave glider. View this vide to see how it works: http://liquidr.com

References

Baumgartner, M. F., Fratantoni, D. M., Hurst, T. P., Brown, M. W., Cole, T. V. M., Van Parijs, S. M. & Johnson, .M. (2013).
  Real-time reporting of baleen whale passive acoustic detections from ocean gliders. Journal of the Acoustical Society of America134(3), 1814-1823
Blidberg, D.R. (2001). The Development of Autonomous Underwater Vehicles (AUVs); A Brief Summary. International
  Conference on Robotics and Automation (ICRA), Seoul, Korea.
German, C.R., Bennett, S.A., Connelly, D.P., Evans, A.J., Murton, B.J., Parson, L.M., Prien, R.D.,Ramirez-Llodra, E., Jakuba,
  M., Shank, T.M., Yoerger, D.R., Baker, E.T., Walker, S.L. & Nakamura, K. (2008). Hydrothermal activity on the southern Mid-Atlantic Ridge: tectonically- and volcanically-controlled venting at 4–5°S. Earth and Planetary Science Letters273, 332–344.
Graham, A.G.C., Dutrieux, P., Vaughan, D.G., Nitsche, F.O., Gyllencreutz, R., Greenwood, S.L., Larter, R.D. & Jenkins, A.
  (2013). Seabed corrugations beneath an Antarctic ice shelf revealed by Autonomous Underwater Vehicle survey: origin and implications for the history of Pine Island Glacier. Journal of Geophysical Research118, 1356–1366.
Nakamura, K., Toki, T., Mochizuki, N., Asada, M., Ishibashi, J., Nogi, Y., Yoshikawa, S.,Miyazaki, J. & Okino, K. (2013).
  Discovery of a new hydrothermal vent based on an underwater, high-resolution geophysical survey. Deep-Sea Research I74, 1–10.
Nakazawa, T., Ushio, M. & Kondoh, M. (2011). Scale dependence of predator–prey mass ratio: determinants and applications.
  Advances in Ecological Research45, 269–302.
Wynn, R.B., Huvenne,V.A., Le Bas,T.P., Murton, B.J., Connelly, D.P., Bett, B.K., Hunt, J.E. & Ruhl, H.A. (2014). Autonomous
  Underwater Vehicles (AUVs): their past, present and future contributions to the advancement of marine geoscience. Marine Geology352, 451-468.

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