KIT | KIT-Bibliothek | Impressum
Open Access Logo
§
Volltext
DOI: 10.5445/IR/1000081117

Deep-Sea Model-Aided Navigation Accuracy for Autonomous Underwater Vehicles Using Online Calibrated Dynamic Models

Oertel, David

Abstract (englisch):
In this work, the accuracy of inertial-based navigation systems for autonomous underwater vehicles (AUVs) in typical mapping and exploration missions up to 5000m depth is examined. The benefit of using an additional AUV motion model in the navigation is surveyed.

Underwater navigation requires acoustic positioning sensors. In this work, so-called Ultra-Short-Baseline (USBL) devices were used allowing the AUV to localize itself relative to an opposite device attached to a (surface) vehicle. Despite their easy use, the devices' absolute positioning accuracy decreases proportional to range. This makes underwater navigation a sophisticated estimation task requiring integration of multiple sensors for inertial, orientation, velocity and position measurements.

First, error models for the necessary sensors are derived. The emphasis is on the USBL devices due to their key role in navigation - besides a velocity sensor based on the Doppler effect. The USBL model is based on theoretical considerations and conclusions from experimental data.
The error models and the navigation algorithms are evaluated on real-world data collected duri ... mehr


Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Hochschulschrift
Jahr 2018
Sprache Englisch
Identifikator URN: urn:nbn:de:swb:90-811172
KITopen ID: 1000081117
Verlag Karlsruhe
Umfang XI, 196 S.
Abschlussart Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Anthropomatik und Robotik (IAR)
Prüfungsdatum 05.02.2018
Referent/Betreuer Prof. H. Wörn
URLs Diese Dissertation ist auch im Verlag Dr. Hut erhältlich.
Schlagworte Robotics, Underwater, Navigation, Localization, Dynamic Modelling, Model-Aided Navigation, AUV, USBL
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft KITopen Landing Page