Name
Abstract | ||
|---|---|---|
We propose a real-time, low-drift laser odometry approach that tightly integrates sequentially measured 3D multi-beam LIDAR data with inertial measurements. The laser measurements are motion-compensated using a novel algorithm based on non-rigid registration of two consecutive laser sweeps and a local map. IMU data is being tightly integrated by means of factor-graph optimization on a pose graph. We evaluate our method on a public dataset and also obtain results on our own datasets that contain information not commonly found in existing datasets. At the time of writing, our method was ranked within the top five laser-only algorithms of the KITTI odometry benchmark. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-12939-2_5 | GCPR |
Field | DocType | Citations |
Inertial frame of reference,Computer vision,Graph,Ranking,Computer science,Motion compensation,Odometry,Laser,Lidar,Artificial intelligence,Inertial measurement unit | Conference | 1 |
PageRank | References | Authors |
0.36 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frank Neuhaus | 1 | 24 | 4.08 |
| Tilman Koß | 2 | 1 | 0.70 |
| Robert Kohnen | 3 | 1 | 0.36 |
| Dietrich Paulus | 4 | 377 | 71.34 |