MulRan Dataset for Urban Place Recognition

Highlights of the dataset

1. Multimodal range sensors: Radar and LiDAR → for robust structural place recognition algorithms
   • data examples
2. Multiple cities (multi-environments) → for environment-free loop detection algorithms
3. Multiple times with month-level temporal gaps → for long-term localization research
4. Multiple loop candidates, particularly
   • Reverse revisits → for rotation (viewpoint) invariant loop detection research
   • Revisits with lane-level differences → for translation change-robust loop detection research
5. 6D baseline trajectories are provided for all sequences → not only place recognition, but also for odometry or SLAM studies.

Data Format (TBA)

• LiDAR
  • binary (same as KITTI)
• Radar (polar image)
  • a single scan with a single time (at the last ray)
• Radar (ray)
  • each ray has corresponding time