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Title: Ocean glider path planning based on automatic structure detection and tracking
Authors: Hernandez, Daniel 
Adler, Leonhard 
Smith, Ryan N.
Eichhorn, Mike
Cabrera, Jorge 
Isern, Josep 
Dominguez, Antonio C. 
Prieto Marañón, Víctor 
UNESCO Clasification: 120304 Inteligencia artificial
120326 Simulación
Keywords: Ocean gliders
Feature detection
Model assessment
Path planning
Issue Date: 2015
Publisher: Springer 
Project: Planificación y Navegación de Vehículos Autónomos Submarinos: Asimilación y Validación de Modelos Oceánicos en 3D de Escala Regional en Aguas Del Archipiélago Canario. 
Journal: Lecture Notes in Computer Science 
Conference: 15th International Conference on Computer Aided Systems Theory, (EUROCAST 2015)
Abstract: While traditional glider path planning relies on constant model forecasts with only a limited range, a new approach to glider operation is based on automated topographical understanding incorporating feature detection and tracking techniques. Encapsulating the key elements of ocean structure dynamics and focusing on their behaviour an alternative prediction data model can be developed. This feature-based characterization is then used to improve upon the glider path planning. Additionally a structural comparison of ROMs and global models is conducted as well as a forecast assessment within the model. This approach is applied to the case of mesoscale eddies that form around the canary islands and spin off describing various trajectories depending on origin, type and time of the year.
ISBN: 978-3-319-27339-6
ISSN: 0302-9743
DOI: 10.1007/978-3-319-27340-2_88
Source: Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science, v. 9520 LNCS, p. 714-719
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