Name
Abstract | ||
|---|---|---|
Simultaneous Localization and Mapping (SLAM) aims to estimate the maximum likelihood map and robot pose based on a robot's control and sensor measurements. In structured environments, such as human environments, we might have additional domain knowledge that could be applied to produce higher quality mapping results. We present a method for using virtual measurements, which are measurements between two features in our map. To demonstrate this, we present a system that uses such virtual measurements to relate visually detected points to walls detected with a laser scanner. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ROBOT.2010.5509497 | Robotics and Automation |
Keywords | Field | DocType |
SLAM (robots),image sensors,maximum likelihood estimation,pose estimation,SLAM,domain knowledge,human environment,laser scanner,maximum likelihood map,robot pose,sensor measurement,simultaneous localization and mapping,virtual measurement | Robot control,Computer vision,Laser scanning,Image sensor,Domain knowledge,Feature extraction,Pose,Artificial intelligence,Engineering,Robot,Simultaneous localization and mapping | Conference |
Volume | Issue | ISSN |
2010 | 1 | 1050-4729 E-ISBN : 978-1-4244-5040-4 |
ISBN | Citations | PageRank |
978-1-4244-5040-4 | 9 | 0.60 |
References | Authors | |
11 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander J. B. Trevor | 1 | 114 | 7.08 |
| John Rogers | 2 | 108 | 16.07 |
| Carlos Nieto-Granda | 3 | 50 | 7.37 |
| Henrik I. Christensen | 4 | 2848 | 235.82 |
| Rogers, J.G. | 5 | 9 | 0.60 |
| Nieto, C. | 6 | 9 | 0.60 |