Name
Abstract | ||
|---|---|---|
Existing approaches for indoor mapping are often either time-consuming or inaccurate. This paper presents the Continuous Normal Distributions Transform (C-NDT), an efficient approach to 3D indoor mapping that balances acquisition time, completeness and accuracy by registering scans acquired from a rotating LiDAR sensor mounted on a moving vehicle. C-NDT uses the robust Normal Distributions Transform (NDT) algorithm for scan registration, ensuring that the mapping is independent of the long-term quality of the odometry. We demonstrate that C-NDT produces more accurate maps than stand-alone dead-reckoning, achieves better map completeness than static scanning and is at least an order of magnitude faster than existing static scanning methods. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IPIN.2012.6418889 | Indoor Positioning and Indoor Navigation |
Keywords | Field | DocType |
distance measurement,indoor radio,mobile radio,normal distribution,optical radar,sensors,transforms,C-NDT algorithm,acquisition time,continuous normal distributions transform,dead-reckoning,map completeness,mobile 3D indoor mapping,moving vehicle,odometry,rotating LiDAR sensor,scan registration,static scanning | Mobile radio,Computer vision,Normal distribution,Moving vehicle,Mobile 3d,Nondestructive testing,Odometry,Electronic engineering,Lidar,Artificial intelligence,Engineering,Completeness (statistics) | Conference |
ISSN | ISBN | Citations |
2162-7347 | 978-1-4673-1955-3 | 3 |
PageRank | References | Authors |
0.40 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. J. Campbell | 1 | 145 | 8.47 |
| Mark Whitty | 2 | 3 | 0.40 |
| Samsung Lim | 3 | 68 | 12.02 |