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Robust Localization and Landing for Autonomous Unmanned Aerial Vehicles in Maritime Environments

This thesis presents methods for robust precision landing of unmanned air vehicles (UAVs) on platforms at sea. Localization methods are proposed for UAV-to-boat state estimation for systems that employ real- time kinematic (RTK) global navigation satellite system (GNSS) and vision sensors. Solutions for GNSS-only are first presented, followed by the fusion of GNSS and vision. The important problem of sensor intrinsic calibration is solved with a novel offline batch estimation approach. Hardware results are presented for all methods. Our calibration of GNSS-to-camera is shown to estimate sensor offsets with millimeter level accuracy. Localization systems are combined with custom state machines that manage the landing attempt via a novel descent cone. This conical threshold enforces a safe and accurate landing. Our landing methods are demonstrated in real-world experiments and achieve consistent accurate landings with error below 10 cm. The fusion of camera and RTK is shown to produce a robust landing system with redundant localization sources.

Identiferoai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-11072
Date16 August 2023
CreatorsJordan, Alexander D.
PublisherBYU ScholarsArchive
Source SetsBrigham Young University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations
Rightshttps://lib.byu.edu/about/copyright/

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