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Pölzleitner, Daniel (2022) AI-Based Vehicle State Estimation Using Inertial and Perception Sensors. Master's, Technische Universität München.
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| Item URL in elib: | https://elib.dlr.de/189399/ | ||||||||
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| Document Type: | Thesis (Master's) | ||||||||
| Title: | AI-Based Vehicle State Estimation Using Inertial and Perception Sensors | ||||||||
| Authors: |
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| Date: | 2022 | ||||||||
| Refereed publication: | No | ||||||||
| Open Access: | No | ||||||||
| Status: | Published | ||||||||
| Keywords: | AI based State Estimation; vehicle state estimation; recurrent neural networks; vehicle side-slip angle estimation | ||||||||
| Institution: | Technische Universität München | ||||||||
| Department: | Lehrstuhl für Hochleistungs-Umrichtersysteme | ||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||
| HGF - Program: | Transport | ||||||||
| HGF - Program Themes: | Road Transport | ||||||||
| DLR - Research area: | Transport | ||||||||
| DLR - Program: | V ST Straßenverkehr | ||||||||
| DLR - Research theme (Project): | V - V&V4NGC - Methoden, Prozesse und Werkzeugketten für die Validierung & Verifikation von NGC | ||||||||
| Location: | Oberpfaffenhofen | ||||||||
| Institutes and Institutions: | Institute of System Dynamics and Control > Vehicle System Dynamics | ||||||||
| Deposited By: | Ruggaber, Julian | ||||||||
| Deposited On: | 31 Oct 2022 09:18 | ||||||||
| Last Modified: | 31 Oct 2022 09:18 |
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