Blar i Institutt for marin teknikk på forfatter "Rajan, Kanna"

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    • Adaptive Sampling for Marine Robotics 

      Fossum, Trygve Olav (Doctoral theses at NTNU;2019:196, Doctoral thesis, 2019)
      Maintaining a healthy ocean is of the utmost importance. Having only a limited set of resources available to study this vast domain requires research and science to focus on more efficient data collection. Determining when ...

    • Advancing Ocean Observation with an AI-driven Mobile Robotic Explorer 

      Saad, Aya; Stahl, Annette; Våge, Andreas; Davies, Emlyn John; Nordam, Tor; Aberle-Malzahn, Nicole; Ludvigsen, Martin; Johnsen, Geir; Sousa, João; Rajan, Kanna (Journal article; Peer reviewed, 2020)
      Rapid assessment and enhanced knowledge of plankton communities and their structure in the productive upper water column is of crucial importance to understand the impact of the changing climate on upper ocean processes. ...

    • Compact models for adaptive sampling in marine robotics 

      Fossum, Trygve Olav; Ryan, John; Mukerji, Tapan; Eidsvik, Jo; Maughan, Thom; Ludvigsen, Martin; Rajan, Kanna (Journal article; Peer reviewed, 2019)
      Finding high-value locations for in situ data collection is of substantial importance in ocean science, where diverse bio-physical processes interact to create dynamically evolving phenomena. These cover a variable spatial ...

    • Field Report: Exploring Fronts with Multiple Robots 

      Costa, Maria; Pinto, José; Dias, Paulo Sousa; Pereira, Joao; Lima, Keila; Ribeiro, Manuel; Sousa, Joao Borges; Lukaczyk, Trent; Mendes, Renato; Tomasino, Maria Paola; Magalhaes, Catarina; Belkin, Igor; Lopez-Castejon, Francisco; Gilabert, Javier; Skarpnes, Kay Arne; Ludvigsen, Martin; Rajan, Kanna; Mirmalek, Zara; Chekalyuk, Alexander (Chapter, 2018)
      This paper presents a report from a cruise onboard the R/V Falkor oceanographic vessel from the Schmidt Ocean Institute. The goal of this cruise was to demonstrate a novel approach to observe the ocean with multiple ...

    • Information-driven robotic sampling in the coastal ocean 

      Fossum, Trygve Olav; Eidsvik, Jo; Ellingsen, Ingrid H.; Alver, Morten; Fragoso, Glaucia Moreira; Johnsen, Geir; mendes, renato; Ludvigsen, Martin; Rajan, Kanna (Journal article; Peer reviewed, 2018)
      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 ...

    • Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling 

      Fossum, Trygve Olav; Travelletti, Cedric; Eidsvik, Jo; Ginsbourger, David; Rajan, Kanna (Journal article, 2021)
      Improving and optimizing oceanographic sampling is a crucial task for marine science and maritime resource management. Faced with limited resources in understanding processes in the water column, the combination of statistics ...

    • Physical controls on phytoplankton size structure, photophysiology and suspended particles in a Norwegian biological hotspot 

      Fragoso, Glaucia Moreira; Davies, Emlyn John; Ellingsen, Ingrid H.; Chauton, Matilde Skogen; Fossum, Trygve Olav; Ludvigsen, Martin; Steinhovden, Kristine; Rajan, Kanna; Johnsen, Geir (Peer reviewed; Journal article, 2019)
      The impact of the physical environment and phytoplankton size on particle types (zooplankton, biogenic matter or phytodetritus) in the water column is poorly understood. Here, we investigate how hydrography (e.g. water ...

    • Toward adaptive robotic sampling of phytoplankton in the coastal ocean 

      Fossum, Trygve Olav; Fragoso, Glaucia Moreira; Davies, Emlyn John; Ullgren, Jenny; Mendes, Renato; Johnsen, Geir; Ellingsen, Ingrid H.; Eidsvik, Jo; Ludvigsen, Martin; Rajan, Kanna (Journal article; Peer reviewed, 2019)
      Currents, wind, bathymetry, and freshwater runoff are some of the factors that make coastal waters heterogeneous, patchy, and scientifically interesting—where it is challenging to resolve the spatiotemporal variation within ...