Autonomous Surface/Subsurface Survey System Field Trials

Phillips, Alexander B.; Salavasidis, Georgios; Kingsland, Matt; Harris, Catherine A.; Pebody, Miles; Templeton, Daniel Roper Robert; McPhail, S.D.; Wood, Terry; P, Taylor, R; Jones, Tiefion

doi:10.1109/auv.2018.8729740

Cited by 11 publications

(7 citation statements)

References 20 publications

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“…Because of their surface expression, ASVs developed for long-term data collection often use solar panels to extend mission durations, which can be up to 1 year (Villareal and Wilson, 2014), supporting payload power budgets on the order of 30 W. Some ASVs have been fitted with acoustic sensors for bathymetric surveys 12 or measuring current velocity and biomass, 13 as well as BGC sensors to study upwelling and frontal region dynamics 14 (Chavez et al, 2018) and measure carbon exchange between ocean and atmosphere. 15 Long-endurance ASVs are also envisioned as communication relays for other subsea platforms (German et al, 2012;Ludvigsen et al, 2016;Phillips et al, 2018).…”

Section: Surface Vehiclesmentioning

confidence: 99%

“…Both civilian and military researchers are considering the design of interoperable AUVs (Carrera et al, 2016;Constanzi et al, 2018;Phillips et al, 2018). Current work is focused on increasing the autonomy of AUVs and Autonomous Surface Vehicles (ASVs) and developing standards for interoperability between heterogeneous platforms to decrease the requirement for complex specialized platforms.…”

Section: Platform Coordinationmentioning

confidence: 99%

“…19 Several institutions are making progress toward integrated systems of heterogeneous platforms focusing on persistence in the maritime environment 20 (Braga et al, 2017;Schmidt Ocean Institute, 2018). Many experiments have demonstrated heterogenous networks of autonomous platforms working together (Schofield et al, 2010;Huet and Mastroddi, 2016;Centurioni et al, 2017;Lindstrom et al, 2017;Marques et al, 2018;Phillips et al, 2018;Testor et al, 2018). Military trials, as depicted in Figure 5, also demonstrated interoperable communications using a standard protocol for underwater digital acoustic communications (LePage et al, 2015), and adaptation of sensors and systems based on real-time environmental conditions (LePage, 2018).…”

Section: Platform Coordinationmentioning

confidence: 99%

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Future Vision for Autonomous Ocean Observations

Whitt¹,

Pearlman²,

Polagye

et al. 2020

Front. Mar. Sci.

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Whitt et al. Future of Autonomous Ocean Observations reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as emerging glider operations (EGO) should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

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Section: Surface Vehiclesmentioning

confidence: 99%

Section: Platform Coordinationmentioning

confidence: 99%

Section: Platform Coordinationmentioning

confidence: 99%

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Future Vision for Autonomous Ocean Observations

Whitt¹,

Pearlman²,

Polagye

et al. 2020

Front. Mar. Sci.

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“…Underwater communication channels, such as acoustic modems are very limited in range, with limited application to over-the-horizon operations. The use of Unmanned Surface Vehicles, acting as acoustic communications gateways to LRAUVs is a promising area of ongoing research (German et al, 2012;Phillips et al, 2018) (see Figure 1D). However, the need for a second vehicle type increases piloting complexity and mission risk.…”

Section: Diverse Platform Typesmentioning

confidence: 99%

Oceanids C2: An Integrated Command, Control, and Data Infrastructure for the Over-the-Horizon Operation of Marine Autonomous Systems

et al. 2020

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Long-range Marine Autonomous Systems (MAS), operating beyond the visual line-of-sight of a human pilot or research ship, are creating unprecedented opportunities for oceanographic data collection. Able to operate for up to months at a time, periodically communicating with a remote pilot via satellite, long-range MAS vehicles significantly reduce the need for an expensive research ship presence within the operating area. Heterogeneous fleets of MAS vehicles, operating simultaneously in an area for an extended period of time, are becoming increasingly popular due to their ability to provide an improved composite picture of the marine environment. However, at present, the expansion of the size and complexity of these multi-vehicle operations is limited by a number of factors: (1) custom control-interfaces require pilots to be trained in the use of each individual vehicle, with limited cross-platform standardization; (2) the data produced by each vehicle are typically in a custom vehicle-specific format, making the automated ingestion of observational data for near-real-time analysis and assimilation into operational ocean models very difficult; (3) the majority of MAS vehicles do not provide machine-to-machine interfaces, limiting the development and usage of common piloting tools, multi-vehicle operating strategies, autonomous control algorithms and automated data delivery. In this paper, we describe a novel piloting and data management system (C2) which provides a unified web-based infrastructure for the operation of long-range MAS vehicles within the UK's National Marine Equipment Pool. The system automates the archiving, standardization and delivery of near-real-time science data and associated metadata from the vehicles to end-users and Global Data Assembly Centers mid-mission. Through the use and promotion of standard data formats and machine interfaces throughout the C2 system, we seek to enable future opportunities to collaborate with both the marine science and robotics communities to maximize the delivery of high-quality oceanographic data for world-leading science.

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“…In the case of the LBL, the vehicle can self‐localise with respect to a set of moored beacons or, in case of SBL and USBL, a support‐ship or an unmanned surface vehicle can be used (Mandt et al, 2001; A. B. Phillips et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments

Salavasidis

Fenucci

Harris

et al. 2020

Journal of Field Robotics

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Deploying long-range autonomous underwater vehicles (AUVs) mid-water column in the deep ocean is one of the most challenging applications for these submersibles. Without external support and speed over the ground measurements, dead-reckoning (DR) navigation inevitably experiences an error proportional to the mission range and the speed of the water currents. In response to this problem, a computationally feasible and lowpower terrain-aided navigation (TAN) system is developed. A Rao-Blackwellized Particle Filter robust to estimation divergence is designed to estimate the vehicle's position and the speed of water currents. To evaluate performance, field data from multiday AUV deployments in the Southern Ocean are used. These form a unique test case for assessing the TAN performance under extremely challenging conditions. Despite the use of a small number of low-power sensors and a Doppler velocity log to enable TAN, the algorithm limits the localisation error to within a few hundreds of metres, as opposed to a DR error of 40 km, given a 50 m resolution bathymetric map. To evaluate further the effectiveness of the system under a varying map quality, grids of 100, 200, and 400 m resolution are generated by subsampling the original 50 m resolution map. Despite the high complexity of the navigation problem, the filter exhibits robust and relatively accurate behaviour. Given the current aim of the oceanographic community to develop maps of similar resolution, the results of this study suggest that TAN can enable AUV operations of the order of months using global bathymetric models.

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Autonomous Surface/Subsurface Survey System Field Trials

Cited by 11 publications

References 20 publications

Future Vision for Autonomous Ocean Observations

Future Vision for Autonomous Ocean Observations

Oceanids C2: An Integrated Command, Control, and Data Infrastructure for the Over-the-Horizon Operation of Marine Autonomous Systems

Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments

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