The Autonomous Racing Software Stack of the KIT19d
Sherif Nekkah, Josua Janus, Mario Boxheimer, Lars Ohnemus, Stefan, Hirsch, Benjamin Schmidt, Yuchen Liu, David Borb\'ely, Florian Keck,, Katharina Bachmann, Lukasz Bleszynski

TL;DR
This paper details the software architecture of KA-RaceIng's autonomous race car for the 2019 Formula Student Driverless competition, highlighting system modules, development methods, and performance results.
Contribution
It provides a comprehensive overview of the software stack for autonomous racing, including perception, localization, mapping, planning, and control, with insights into implementation and performance.
Findings
System modules successfully integrated for autonomous racing
Achieved competitive performance in 2019 competitions
Runtime measurements demonstrate real-time capabilities
Abstract
Formula Student Driverless challenges engineering students to develop autonomous single-seater race cars in a quest to bring about more graduates who are well-prepared to solve the real world problems associated with autonomous driving. In this paper, we present the software stack of KA-RaceIng's entry to the 2019 competitions. We cover the essential modules of the system, including perception, localization, mapping, motion planning, and control. Furthermore, development methods are outlined and an overview of the system architecture is given. We conclude by presenting selected runtime measurements, data logs, and competition results to provide an insight into the performance of the final prototype.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
