Breakdown and components of AUV

The concept of AUVs has been in development over the past few decades, however there have been rapid advances in recent years. An early example of an unmanned surface vessel is from 1996-97 of MIT’s AutoCat and the HUGIN project in the early 1990s. Existing and robust technologies are integrated into AUVs to give them functionality and make them appropriate for certain applications such as bathymetry and surveying. These technologies include SONAR and positioning methods long baseline (LBL) and ultra short baseline (USBL). While these are acoustic positioning, another category of positioning technologies are inertial which involve measurements of the vessel’s velocity and directions. Improvements in inertial and acoustic positioning technologies has enabled the further autonomy and development of AUVs.

The drive for the development of AUVs has come from military and research. The US navy has had their master plan for UUV documented in 2000.  There have been projects using USV as supporting navigation for AUVs by LBL in 2007. Building AUVs can be done by adding controls, navigation and telemetry to any small craft. Initial prototypes used old military missiles with a higher dependence on telemetry control that would be considered an ROV. The use of AUVs are promising for defence and science.

The makeup of AUVs can be broken down into certain components. They would have different functions but can also work together as a check. Here we can look at the groups of positioning, data collection and sensors, mapping and navigation as well as some platforms and vessels they operate on. Positioning components that can be used are LBL, USBL, Doppler velocity log (DVL) and IMU. Some of these can be combined to improve performance. Data collection sensors can include acoustic Doppler current profiler(ADCP), side scan sonar, multibeam echo sounders and optical methods and cameras. These are referred to as payload sensors in AUV specifications. Mapping and navigation can include robotics and computer based processes such as SLAM and its different forms. These are computer processes as they are made up of algorithms using input data to produce obstacle avoidance, filtering and real-time mapping. Finally, platforms can be in surface vessels and underwater missile models made by a number of companies. Some of these parts will be explained below.

flow diagram
Figure: Example breakdown of an AUV

Positioning:

LBL systems use a network of at least three acoustic beacons with predetermined known locations. These are sparsely spread along the seafloor to create the long baseline. The AUV can then infer its position by triangulating measurements to each of the beacons. This system can also be deployed using GPS intelligent buoys on which the acoustic beacons are installed. Beacon locations are determined by GPS.

USBL use a single beacon with a single receiver on the hull of the surface ship. The receiver can get its position through the phase differences from the beacon, from which an AUV can get it position relative to the ship.

ADCP uses Doppler shift, which measures the change in pitch of the returned echo from scattering by particles in the current. This allows the system to measure water currents in the water column. DVL can work alongside the ADCP and can log the velocity of the vessel through data from the ADCP. This as an inertial system will track the position of the vessel.

Data collection:

Sidescan sonar (SSS), previously been utilized with the use of  an underwater towfish by a ship, can be placed directly on the AUV. These collect data line by line to produce an acoustic image of the seabed. As the AUV is a more stable platform aids in the progress and use of Synthetic aperture sonar as an improved option to SSS.

Multibeam echo sounder as an extension of the single beam which directs a single beam vertically and receives its response. The multibeam transmits a fan of beams. The high resolution systems would be used for local surveys and suitable because of their small size.

Navigation:

SLAM as mentioned is a concept from above ground robotics. When applied in AUVs these processes can increase autonomy from smarter systems. This can make path planning a more dynamic and responsive and involves partial data processing to be fed back to the vehicle. Two SLAM processes are feature based and view based where an autonomous vehicle can get its location relative to a number of recognised features or takes a whole sweep view and compare to previous views to get an updated location. This is a recent concept applied to AUVs to increase autonomy.

Major models and companies:

Teledyne: http://www.teledynemarine.com/gavia-offshore-surveyor?BrandID=9

ASV Ltd.: http://asvglobal.com/product/c-worker-7/

Liquid Robotics (Wave Glider): https://www.liquid-robotics.com/platform/overview/

Hugin(Konsberg maritime): https://www.km.kongsberg.com/ks/web/nokbg0240.nsf/AllWeb/B3F87A63D8E419E5C1256A68004E946C?OpenDocument

References:

Lurton, X 2008, An Introduction to Underwater Acoustics, Springer

Paull, L., Saeedi, S., Seto, M., & Li, H. (2014). AUV navigation and localization: A review. IEEE Journal of Oceanic Engineering, 39(1), 131-149.

E. Manley, “Unmanned surface vehicles, 15 years of development,” OCEANS 2008, Quebec City, QC, 2008, pp. 1-4.

US navy Master plan : http://www.navy.mil/navydata/technology/usvmppr.pdf

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