Name
Abstract | ||
|---|---|---|
One of the greatest obstacles to the use of Simultaneous Localization And Mapping (SLAM) in a real-world environment is the need to maintain the full correlation structure between the vehicle and all of the landmark estimates. This structure is computationally ... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.robot.2006.06.005 | Robotics and Autonomous Systems |
Keywords | Field | DocType |
SLAM,Consistency,Extended Kalman filter,Robocentric,Map joining,Linearization errors | Computer vision,Extended Kalman filter,Local map,Computer science,Artificial intelligence,Mapping algorithm,Simultaneous localization and mapping,Robot,Limiting,Linearization | Journal |
Volume | Issue | ISSN |
55 | 1 | Robotics and Autonomous Systems |
Citations | PageRank | References |
88 | 3.85 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. A. Castellanos | 1 | 211 | 32.55 |
| Ruben Martinez-cantin | 2 | 310 | 18.86 |
| Juan Domingo | 3 | 3319 | 258.54 |
| J. Neira | 4 | 509 | 39.39 |