Lidar-based Mapping and Localization for Autonomous Racing

Markus Schratter*, Jasmina Zubača, Konstantin Lassnig, Tobias Renzler, Martin Kirchengast, Stefan Loigge, Michael Stolz, Daniel Watzenig

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: KonferenzbeitragPaperBegutachtung


Autonomous racing challenges, since the very beginning of automated driving, have inspired new development and defined state of the art. By this, autonomous racing has strongly contributed to the research field of automated driving and indirectly generated important societal impact, increasing traffic safety by reducing or even avoiding human errors in driving. Accurate, reliable and robust perception is a key factor for driverless vehicles, and lidar sensor is currently one of the most promising sensor technologies used for environmental perception. A lidar sensor is versatile as it can be used for mapping purposes, object detection and for the localization. This makes it predestined for many automotive applications. In this publication, the Autonomous Racing Graz team reveals their approaches for mapping and localization using only a lidar sensor, and the modified software components from Autoware. Developed solutions are applied and validated in two ROBORACE Season Alpha challenges. The entire process, from mapping, over path planning, to online localization, is summarized and discussed.
PublikationsstatusVeröffentlicht - Mai 2021
VeranstaltungOpportunities and Challenges with Autonomous Racing: 2021 ICRA Workshop -
Dauer: 31 Mai 2021 → …


WorkshopOpportunities and Challenges with Autonomous Racing
Zeitraum31/05/21 → …


Untersuchen Sie die Forschungsthemen von „Lidar-based Mapping and Localization for Autonomous Racing“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren