5 papers · 1 filter
FAR-LIO: Enabling High-Speed Autonomy through Fast, Accurate, and Robust LiDAR-Inertial Odometry
Maximilian Leitenstern, Marcel Weinmann, Patrick Haft +3
Robust and accurate odometry estimation is essential in modern robotics. In environments characterized by highly dynamic motion and sensor noise, odometry estimation becomes increa…
Head-to-Head autonomous racing at the limits of handling in the A2RL challenge
Simon Hoffmann, Simon Sagmeister, Tobias Betz +17
Autonomous racing presents a complex challenge involving multi-agent interactions between vehicles operating at the limit of performance and dynamics. As such, it provides a valuab…
FlexCloud: Direct, Modular Georeferencing and Drift-Correction of Point Cloud Maps
Maximilian Leitenstern, Marko Alten, Christian Bolea-Schaser +3
Current software stacks for real-world applications of autonomous driving leverage map information to ensure reliable localization, path planning, and motion prediction. An importa…
OpenLiDARMap: Zero-Drift Point Cloud Mapping using Map Priors
Dominik Kulmer, Maximilian Leitenstern, Marcel Weinmann +1
Accurate localization is a critical component of mobile autonomous systems, especially in Global Navigation Satellite Systems (GNSS)-denied environments where traditional methods f…
FlexMap Fusion: Georeferencing and Automated Conflation of HD Maps with OpenStreetMap
Maximilian Leitenstern, Florian Sauerbeck, Dominik Kulmer +1
Today's software stacks for autonomous vehicles rely on HD maps to enable sufficient localization, accurate path planning, and reliable motion prediction. Recent developments have…