6 papers
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…
CaLiV: LiDAR-to-Vehicle Calibration of Arbitrary Sensor Setups
Ilir Tahiraj, Markus Edinger, Dominik Kulmer +1
In autonomous systems, sensor calibration is essential for safe and efficient navigation in dynamic environments. Accurate calibration is a prerequisite for reliable perception and…
vEDGAR -- Can CARLA Do HiL?
Nils Gehrke, David Brecht, Dominik Kulmer +2
Simulation offers advantages throughout the development process of automated driving functions, both in research and product development. Common open-source simulators like CARLA a…
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…
Multi-LiCa: A Motion and Targetless Multi LiDAR-to-LiDAR Calibration Framework
Dominik Kulmer, Ilir Tahiraj, Andrii Chumak +1
Today's autonomous vehicles rely on a multitude of sensors to perceive their environment. To improve the perception or create redundancy, the sensor's alignment relative to each ot…