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Leveraging learned monocular depth prediction for pose estimation and mapping on unmanned underwater vehicles

This paper presents a general framework that integrates visual and acoustic sensor data to enhance localization and mapping in complex, highly dynamic underwater environments, with a particular focus on fish farming. The pipeline enables net-relative pose estimation for Unmanned Underwater Vehicles...

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Autors principals: Marco Job, David Botta, Victor Reijgwart, Luca Ebner, Andrej Studer, Roland Siegwart, Eleni Kelasidi
Format: Artigo
Idioma:Inglês
Publicat: Frontiers Media S.A. 2025-06-01
Col·lecció:Frontiers in Robotics and AI
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Accés en línia:https://www.frontiersin.org/articles/10.3389/frobt.2025.1609765/full
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