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A Self-Driving Car Architecture in ROS2

  • In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions.

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Metadaten
Verfasserangaben:Michael RekeORCiD, Daniel Peter, Joschua Schulte-TiggesORCiD, Stefan SchifferORCiD, Alexander FerreinORCiD, Thomas Walter, Dominik Matheis
DOI:https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020
ISBN:978-1-7281-4162-6
Titel des übergeordneten Werkes (Englisch):2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa
Verlag:IEEE
Verlagsort:New York, NY
Dokumentart:Konferenzveröffentlichung
Sprache:Englisch
Erscheinungsjahr:2020
Datum der Publikation (Server):03.04.2020
Erste Seite:1
Letzte Seite:6
Bemerkung:
2020 International SAUPEC/RobMech/PRASA Conference, 29-31 Jan. 2020, Cape Town, South Africa
Link:https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020
Zugriffsart:weltweit
Fachbereiche und Einrichtungen:FH Aachen / Fachbereich Elektrotechnik und Informationstechnik
FH Aachen / MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik
collections:Verlag / IEEE