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Title:

TUM autonomous motorsport: An autonomous racing software for the Indy Autonomous Challenge

Document type:
Zeitschriftenaufsatz
Author(s):
Betz, J.; Betz, T.; Fent, F.; Geisslinger, M.; Heilmeier, A.; Hermansdorfer, L.; Herrmann, T.; Huch, S.; Karle, P.; Lienkamp, M.; Lohmann, B.; Nobis, F.; Ögretmen, L.; Rowold, M.; Sauerbeck, F.; Stahl, T.; Trauth, R.; Werner, F.; Wischnewski, A.
Abstract:
For decades, motorsport has been an incubator for innovations in the automotive sector and brought forth systems, like, disk brakes or rearview mirrors. Autonomous racing series such as Roborace, F1Tenth, or the Indy Autonomous Challenge (IAC) are envisioned as playing a similar role within the autonomous vehicle sector, serving as a proving ground for new technology at the limits of the autonomous systems capabilities. This paper outlines the software stack and approach of the TUM Autonomous Mo...     »
Keywords:
artificial intelligence; autonomous robot; dynamic obstacle avoidance; unmanned ground vehicle; vehicle robot
Journal title:
Journal of Field Robotics
Year:
2023
Year / month:
2023-01
Quarter:
1. Quartal
Month:
Jan
Pages contribution:
pp. 1-27
Covered by:
; Scopus; Web of Science
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1002/rob.22153
WWW:
https://doi.org/10.1002/rob.22153
Publisher:
John Wiley and Sons Inc.
Print-ISSN:
15564959
Submitted:
31.05.2022
Accepted:
19.12.2022
Date of publication:
12.01.2023
Semester:
WS 22-23
TUM Institution:
Lehrstuhl für Regelungstechnik
Ingested:
25.01.2023
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