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Development and Testing of Navigation Algorithms for Autonomous Underwater Vehicles

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  • © 2020

Overview

  • Nominated as an outstanding PhD thesis by University of Florence, Italy
  • Describes novel algorithms for AUV pose and attitude estimation
  • Includes extensive validation results obtained in field tests

Part of the book series: Springer Theses (Springer Theses)

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Table of contents (6 chapters)

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About this book

This book focuses on pose estimation algorithms for Autonomous Underwater Vehicles (AUVs). After introducing readers to the state of the art, it describes a joint endeavor involving attitude and position estimation, and details the development of a nonlinear attitude observer that employs inertial and magnetic field data and is suitable for underwater use. In turn, it shows how the estimated attitude constitutes an essential type of input for UKF-based position estimators that combine position, depth, and velocity measurements. 

The book discusses the possibility of including real-time estimates of sea currents in the developed estimators, and highlights simulations that combine real-world navigation data and experimental test campaigns to evaluate the performance of the resulting solutions. In addition to proposing novel algorithms for estimating the attitudes and positions of AUVs using low-cost sensors and taking into account magnetic disturbances and ocean currents, the book provides readers with extensive information and a source of inspiration for the further development and testing of navigation algorithms for AUVs. 

Authors and Affiliations

  • Department of Industrial Engineering, University of Florence, Florence, Italy

    Francesco Fanelli

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