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Titel:

Vehicle Dynamics State Estimation and Localization for High Performance Race Cars

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Wischnewski, A.; Stahl, T.; Betz, J.; Lohmann, B.
Seitenangaben Beitrag:
pp. 307-312
Abstract:
Autonomous driving requires accurate information about the vehicle pose and motion state in order to achieve precise tracking of the planned trajectory. In this paper we propose a robust architecture to localize a high performance race car and show experimental results with speeds up to 150 km h-1 and utilizing approximately 80% of the available friction level. The concept has been applied using the development vehicle DevBot taking part in the Roborace competition. To achieve robust and reliabl...     »
Stichworte:
State Estimation; Sensor Fusion; Robust Performance; Autonomous Vehicles; Kalman Filters
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Herausgeber:
Wiszniewski B.; Kowalczuk Z.; Domzalski M.
Kongress- / Buchtitel:
IFAC Symposium on Intelligent Autonomous Vehicles IAV [10th, Gdansk, Poland, 2019]
Kongress / Zusatzinformationen:
IFAC-PapersOnLine
Band / Teilband / Volume:
Vol. 52, Issue 8
Verlag / Institution:
Elsevier
Jahr:
2019
Monat:
Aug
Nachgewiesen in:
Scopus; Web of Science
Serien-ISSN:
24058963
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1016/j.ifacol.2019.08.064
WWW:
https://doi.org/10.1016/j.ifacol.2019.08.064
TUM Einrichtung:
Lehrstuhl für Regelungstechnik
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