Name
Abstract | ||
|---|---|---|
The terrestrial acquisition of 3D point clouds by laser range finders has recently moved to mobile platforms. Measuring the environment while simultaneously moving the vehicle demands a high level of accuracy from positioning systems such as the IMU, GPS and odometry. We present a novel semi-rigid SLAM algorithm that corrects the global position of the vehicle at every point in time, while simultaneously improving the quality and accuracy of the entire acquired map. Using the algorithm the temporary failure of positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of our approach on a wide variety of systems and data sets. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IROS.2012.6385509 | Intelligent Robots and Systems |
Keywords | Field | DocType |
SLAM (robots),edge detection,mobile robots,3D point clouds,6DOF semi-rigid SLAM,GPS,IMU,laser range finders,mobile scanning,odometry,positioning systems,semi-rigid SLAM algorithm,terrestrial acquisition | Computer vision,Computer science,Odometry,Global Positioning System,Artificial intelligence,Inertial measurement unit,Point cloud,Simultaneous localization and mapping,Mobile telephony,Trajectory,Mobile robot | Conference |
ISSN | ISBN | Citations |
2153-0858 | 978-1-4673-1737-5 | 7 |
PageRank | References | Authors |
0.50 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elseberg, J. | 1 | 10 | 0.95 |
| Dorit Borrmann | 2 | 216 | 17.74 |
| Andreas Nüchter | 3 | 1341 | 90.03 |