Online acoustic localization methods for autonomous underwater vehicles
Autonomous Underwater Vehicles (AUVs) true autonomy capabilities in complex unknown environments, have not yet been fully achieved because of the lack of online algorithms that can solve fundamental problems such as localization, mapping and path-planning on-board the AUV. This thesis presents the d...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/664427 |
| Acceso en línea: | http://hdl.handle.net/10803/664427 |
| Access Level: | acceso abierto |
| Palabra clave: | Autonomous underwater vehicles Vehicles submarins autònoms Vehículos submarinos autónomos AUV Simoultaneous localization and mapping Localització i construcció de mapes de forma simultànea Localización y mapeo simultáneo SLAM Hilbert maps Mapes de Hilbert Mapas de Hilbert Kalman filter 68 |
| Sumario: | Autonomous Underwater Vehicles (AUVs) true autonomy capabilities in complex unknown environments, have not yet been fully achieved because of the lack of online algorithms that can solve fundamental problems such as localization, mapping and path-planning on-board the AUV. This thesis presents the development of two online localization algorithms for AUVs. The first algorithm is based on a Sum of Gaussian filter for online range-only localization of a Docking Station for battery recharging and data uploading. This algorithm is tested in a wider project where it is combined with other algorithms to produce a complete homing and docking strategy. The second algorithm proposes an online SLAM framework for continuous occupancy mapping named H-SLAM. It uses a Rao-Blackwellized Particle Filter where each particle carries a Hilbert Map representation of the environment. This algorithm is tested on two real-world datasets offering a significantly better reconstruction of the environment than using DR navigation. |
|---|