Information‐driven robotic sampling in the coastal ocean

Efficient sampling of coastal ocean processes, especially mechanisms such as upwelling and internal waves and their influence on primary production, is critical for understanding our changing oceans. Coupling robotic sampling with ocean models provides an effective approach to adaptively sample such...

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Bibliographic Details
Published in:Journal of field robotics 2018-10, Vol.35 (7), p.1101-1121
Main Authors: Fossum, Trygve Olav, Eidsvik, Jo, Ellingsen, Ingrid, Alver, Morten Omholt, Fragoso, Glaucia Moreira, Johnsen, Geir, Mendes, Renato, Ludvigsen, Martin, Rajan, Kanna
Format: Article
Language:English
Subjects:
Autonomous underwater vehicles
Coastal environments
Coastal processes
Computer simulation
Coupling
Environmental conditions
Gaussian process
Gaussian processes
In situ measurement
Internal waves
marine robotics
Model accuracy
ocean modeling
Ocean models
ocean sampling
Oceans
Primary production
Remote sensing
robotic sampling
Sampling
Satellites
Sea trials
Ships
Underwater vehicles
Upwelling
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Summary:Efficient sampling of coastal ocean processes, especially mechanisms such as upwelling and internal waves and their influence on primary production, is critical for understanding our changing oceans. Coupling robotic sampling with ocean models provides an effective approach to adaptively sample such features. We present methods that capitalize on information from ocean models and in situ measurements, using Gaussian process modeling and objective functions, allowing sampling efforts to be concentrated to regions with high scientific interest. We demonstrate how to combine and correlate marine data from autonomous underwater vehicles, model forecasts, remote sensing satellite, buoy, and ship‐based measurements, as a means to cross‐validate and improve ocean model accuracy, in addition to resolving upper water‐column interactions. Our work is focused on the west coast of Mid‐Norway where significant influx of Atlantic Water produces a rich and complex physical–biological coupling, which is hard to measure and characterize due to the harsh environmental conditions. Results from both simulation and full‐scale sea trials are presented.
ISSN:1556-4959
1556-4967
DOI:10.1002/rob.21805