Radar Odometry Results on MulRan dataset
Radar
- Here, the radar means Navtech radar data.
- For details, see https://oxford-robotics-institute.github.io/radar-robotcar-dataset/
- Radar is robust to occlusions than LiDAR in urban sites.
Yeti Radar Odometry
- Paper
- Do We Need to Compensate for Motion Distortion and Doppler Effects in Spinning Radar Navigation? (ICRA 2021)
- Code
- https://github.com/keenan-burnett/yeti_radar_odometry
- Features
- implemented cen2018, cen2019 method with motion compensation
- Requirements
- need ray-wise timestamps
Tutorial: running Yeti on MulRan dataset
- see this video
- link (TBA)
Results on MulRan dataset
MulRan dataset
- MulRan: Multimodal Range Dataset for Urban Place Recognition (ICRA 2019)
- https://sites.google.com/view/mulran-pr/dataset
Methods
- Cen2018: Precise ego-motion estimation with millimeter-wave radar under diverse and challenging conditions (ICRA 2018)
- Cen2019: Radar-only ego-motion estimation in difficult settings via graph matching (ICRA 2019)
- Left: Cen2018, Right: Cen2019
- The trajectory color means start-blue and red-end.










Comments
ps. for the visualiation code, see https://github.com/gisbi-kim/yeti_odom_drawer ↩︎
ps2. KAIST 01 and Sejong 01 sequences do not provide ray-wise timestamps, so the results are omitted. ↩︎