Radar Odometry Results on MulRan dataset

Radar


Yeti Radar Odometry

  • Paper
    • Do We Need to Compensate for Motion Distortion and Doppler Effects in Spinning Radar Navigation? (ICRA 2021)
  • Code

Tutorial: running Yeti on MulRan dataset

  • see this video
    • link (TBA)

Results on MulRan dataset

  • MulRan 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)
  • Result captures 1 2

    • Left: Cen2018, Right: Cen2019
    • The trajectory color means start-blue and red-end.
KAIST 02

KAIST 03

DCC 01

DCC 02

DCC 03

Riverside 01

Riverside 02

Riverside 03

Sejong 02

Sejong 03


Comments


  1. ps. for the visualiation code, see https://github.com/gisbi-kim/yeti_odom_drawer ↩︎

  2. ps2. KAIST 01 and Sejong 01 sequences do not provide ray-wise timestamps, so the results are omitted. ↩︎

Giseop Kim
Giseop Kim
Assistant Professor

SLAM, 3D Reconstruction, Spatial AI, Physical AI