Assessing the potential of autonomous submarine gliders for ecosystem monitoring across multiple trophic levels (plankton to cetaceans) and pollutants in shallow shelf seas

A combination of scientific, economic, technological and policy drivers is behind a recent upsurge in the use of marine autonomous systems (and accompanying miniaturized sensors) for environmental mapping and monitoring. Increased spatial–temporal resolution and coverage of data, at reduced cost, is particularly vital for effective spatial management of highly dynamic and heterogeneous shelf environments. This proof-of-concept study involves integration of a novel combination of sensors onto buoyancy-driven submarine gliders, in order to assess their suitability for ecosystem monitoring in shelf waters at a variety of trophic levels. Two shallow-water Slocum gliders were equipped with CTD and fluorometer to measure physical properties and chlorophyll, respectively. One glider was also equipped with a single-frequency echosounder to collect information on zooplankton and fish distribution. The other glider carried a Passive Acoustic Monitoring system to detect and record cetacean vocalizations, and a passive sampler to detect chemical contaminants in the water column. The two gliders were deployed together off southwest UK in autumn 2013, and targeted a known tidal-mixing front west of the Isles of Scilly. The gliders’ mission took about 40 days, with each glider travelling distances of >1000 km and undertaking >2500 dives to depths of up to 100 m. Controlling glider flight and alignment of the two glider trajectories proved to be particularly challenging due to strong tidal flows. However, the gliders continued to collect data in poor weather when an accompanying research vessel was unable to operate. In addition, all glider sensors generated useful data, with particularly interesting initial results relating to subsurface chlorophyll maxima and numerous fish/cetacean detections within the water column. The broader implications of this study for marine ecosystem monitoring with submarine gliders are discussed

A concept design for an ultra-long-range survey class AUV

Gliders and flight-style Autonomous Underwater Vehicles (AUVs) are used to perform perform autonomous surveys of large areas of open ocean. Glider missions are characterized by their profiling flight pattern, slow speed, long range (1000s of km) and many month mission duration. Flight-style AUV missions are faster, of shorter range (100s of km) and multi day duration. An AUV combining many aspects of both vehicle classes would be of considerable value.This paper investigates the factors that affect the range of a traditional flight-style AUVs. A generic range model is outlined which factors in the effects of buoyancy on the range. The model shows that to create a very long range AUV it is necessary to reduce the hotel load on the AUV to the order of 1W and to add wings to overcome the vehicle’s positive buoyancy whilst travelling at the reduced speed required for long range.Using this model a concept long range AUV is outlined that is capable of travelling up to 5000km. The practical issues associated with achieving this range are also discussed

Science-driven Autonomous & Heterogeneous Robotic Networks: A Vision for Future Ocean Observations

The goal of this project was to develop the first algorithms that allow a heterogeneous group of oceanic robots to autonomously determine and implement sampling strategies with the help of numerical ocean forecasts and remotely-sensed observations. Two-way feedback with shore-based numerical models, tested in the field, had not previously been attempted. New planning algorithms were tested during two field programs in Monterey Bay during a 12-month period using three different types of autonomous vehicles

A remote anomaly detection system for Slocum underwater gliders

Marine Autonomous Systems (MAS) operating at sea beyond visual line of sight need to be self-reliant, as any malfunction could lead to loss or pose a risk to other sea users. In the absence of fully automated on-board control and fault detection tools, MAS are piloted and monitored by experts, resulting in high operational costs and limiting the scale of observational fleets that can be deployed simultaneously. Hence, an effective anomaly detection system is fundamental to increase fleet capacity and reliability. In this study, an on-line, remote fault detection system is developed for underwater gliders. Two alternative methods are analysed using time series data: feedforward deep neural networks estimating the glider’s vertical velocity and an autoencoder. The systems are trained using field data from four baseline deployments of Slocum gliders and tested on six deployments of vehicles suffering from adverse behaviour. The methods are able to successfully detect a range of anomalies in the near real time data streams, whilst being able to generalise to different glider configurations. The autoencoder’s error in reconstructing the original signals is the clearest indicator of anomalies. Thus, the autoencoder is a prime candidate to be included into an all-encompassing condition monitoring system for MAS

Nonlinear robust integral sliding super-twisting sliding mode control application in autonomous underwater glider

1016-1027The design of a robust controller is a challenging task due to nonlinear behaviour of the glider and surround environment. This paper presents design and simulation of nonlinear robust integral super-twisting sliding mode control for controlling the longitudinal plane of an autonomous underwater glider (AUG). The controller is designed for trajectory tracking problem in existence of external disturbance and parameter variations for pitching angle and net buoyancy of the longitudinal plane of an AUG. The algorithm is designed based on integral sliding mode control and super-twisting sliding mode control. The performance of the proposed controller is compared to original integral sliding mode and original super-twisting algorithm. The simulation results have shown that the proposed controller demonstrates satisfactory performance and also reduces the chattering effect and control effort

Research Brief

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Data Visualization to Evaluate and Facilitate Targeted Data Acquisitions in Support of a Real-time Ocean Forecasting System

A robust evaluation toolset has been designed for Naval Research Laboratory’s Real-Time Ocean Forecasting System RELO with the purpose of facilitating an adaptive sampling strategy and providing a more educated guidance for routing underwater gliders. The major challenges are to integrate into the existing operational system, and provide a bridge between the modeling and operative environments. Visualization is the selected approach and the developed software is divided into 3 packages: The first package is to verify that the glider is actually following the waypoints and to predict the position of the glider for the next cycle’s instructions. The second package helps ensures that the delivered waypoints are both useful and feasible. The third package provides the confidence levels for the suggested path. This software’s implementation is in Python for portability and modularity to allow for easy expansion for new visuals

Autonomous sampling of ocean submesoscale fronts with ocean gliders and numerical model forecasting

Submesoscale fronts arising from mesoscale stirring are ubiquitous in the ocean and have a strong impact on upper-ocean dynamics. This work presents a method for optimizing the sampling of ocean fronts with autonomous vehicles at meso- and submesoscales, based on a combination of numerical forecast and autonomous planning. This method uses a 48-h forecast from a real-time high-resolution data-assimilative primitive equation ocean model, feature detection techniques, and a planner that controls the observing platform. The method is tested in Monterey Bay, off the coast of California, during a 9-day experiment focused on sampling subsurface thermohaline-compensated structures using a Seaglider as the ocean observing platform. Based on model estimations, the sampling “gain,” defined as the magnitude of isopycnal tracer variability sampled, is 50% larger in the feature-chasing case with respect to a non-feature-tracking scenario. The ability of the model to reproduce, in space and time, thermohaline submesoscale features is evaluated by quantitatively comparing the model and glider results. The model reproduces the vertical (~50–200 m thick) and lateral (~5–20 km) scales of subsurface subducting fronts and near-bottom features observed in the glider data. The differences between model and glider data are, in part, attributed to the selected glider optimal interpolation parameters and to uncertainties in the forecasting of the location of the structures. This method can be exported to any place in the ocean where high-resolution data-assimilative model output is available, and it allows for the incorporation of multiple observing platforms

Ocean observations in support of studies and forecasts of tropical and extratropical cyclones

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Domingues, R., Kuwano-Yoshida, A., Chardon-Maldonado, P., Todd, R. E., Halliwell, G., Kim, H., Lin, I., Sato, K., Narazaki, T., Shay, L. K., Miles, T., Glenn, S., Zhang, J. A., Jayne, S. R., Centurioni, L., Le Henaff, M., Foltz, G. R., Bringas, F., Ali, M. M., DiMarco, S. F., Hosoda, S., Fukuoka, T., LaCour, B., Mehra, A., Sanabia, E. R., Gyakum, J. R., Dong, J., Knaff, J. A., & Goni, G. Ocean observations in support of studies and forecasts of tropical and extratropical cyclones. Frontiers in Marine Science, 6, (2019): 446, doi:10.3389/fmars.2019.00446.Over the past decade, measurements from the climate-oriented ocean observing system have been key to advancing the understanding of extreme weather events that originate and intensify over the ocean, such as tropical cyclones (TCs) and extratropical bomb cyclones (ECs). In order to foster further advancements to predict and better understand these extreme weather events, a need for a dedicated observing system component specifically to support studies and forecasts of TCs and ECs has been identified, but such a system has not yet been implemented. New technologies, pilot networks, targeted deployments of instruments, and state-of-the art coupled numerical models have enabled advances in research and forecast capabilities and illustrate a potential framework for future development. Here, applications and key results made possible by the different ocean observing efforts in support of studies and forecasts of TCs and ECs, as well as recent advances in observing technologies and strategies are reviewed. Then a vision and specific recommendations for the next decade are discussed.This study was supported by the National Oceanic and Atmospheric Administration and JSPS KAKENHI (Grant Numbers: JP17K19093, JP16K12591, and JP16H01846)