Test Data & Visualization¶
A reference dataset is provided so you can verify a fresh install and explore the visual output in Rerun.
Dataset¶
The data was recorded by the
TUM Autonomous Motorsport Team
during the Abu Dhabi Autonomous Racing League 2025.
It enables testing the georeferencing executable.
- LiDAR / SLAM trajectory — created with glim.
- Reference trajectory — raw data from the RTK-corrected GNSS signal of the vehicle.
Visualising results in Rerun¶
- Results of the rubber-sheet transformation and the resulting, transformed point cloud map are streamed live to Rerun.
- By default the Rerun viewer instance inside the Docker container is spawned. If you have issues with the viewer and your graphics drivers, launch a Rerun viewer locally instead — FlexCloud will connect to it automatically.
- Adjust the algorithm parameters (see Usage) if results are unsatisfactory.
Entity legend¶
| Entity | Description |
|---|---|
Trajectory |
reference trajectory |
Trajectory_SLAM |
original SLAM trajectory |
Trajectory_align |
SLAM trajectory aligned rigidly to reference |
Trajectory_RS |
SLAM trajectory after rubber-sheet transformation |
Trajectory_align_deviation |
aligned trajectory, per-segment colored by euclidean deviation from the reference (only with --evaluation) |
Trajectory_RS_deviation |
rubber-sheeted trajectory, per-segment colored by euclidean deviation from the reference (only with --evaluation) |
control_points |
control points used for rubber-sheeting |
tetrahedra |
triangulation used for rubber-sheeting |
pcd_map |
transformed point cloud map |
Example output¶
