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.
Navigation Sensors Acoustic Localization Systems AUV Dynamic Model Unscented Kalman Filter Sea Currents Estimation Attitude Estimation AUV Navigation Magnetic Disturbance Underwater Self-localization
- DOI https://doi.org/10.1007/978-3-030-15596-4
- Copyright Information Springer Nature Switzerland AG 2020
- Publisher Name Springer, Cham
- eBook Packages Intelligent Technologies and Robotics Intelligent Technologies and Robotics (R0)
- Print ISBN 978-3-030-15595-7
- Online ISBN 978-3-030-15596-4
- Series Print ISSN 2190-5053
- Series Online ISSN 2190-5061
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