State Estimation in SLAM Techniques for Autonomous Vehicles
The purpose of this thesis is to study the effects of both novel modelling and estimation techniques applied to localization and SLAM problems, which can be divided into the following objectives. Apply state estimation to an autonomous vehicle using a dynamic pseudolinear formulation of the system b...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/329989 |
| Acceso en línea: | https://hdl.handle.net/2117/329989 |
| Access Level: | acceso abierto |
| Palabra clave: | Autonomous vehicles Vehicles autònoms Àrees temàtiques de la UPC::Enginyeria mecànica |
| Sumario: | The purpose of this thesis is to study the effects of both novel modelling and estimation techniques applied to localization and SLAM problems, which can be divided into the following objectives. Apply state estimation to an autonomous vehicle using a dynamic pseudolinear formulation of the system based on LPV theory. Explore the usage of zonotopic based estimation techniques and their advantages with respect to probabilistic Kalman filters. Compare the techniques presented in previous points with classical Extended Kalman filters. Expand the localization problem to SLAM. Provide a testing platform, both in a physical device and in simulation, to verify the algorithms studied. |
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