Name
Abstract | ||
|---|---|---|
Visual localization and mapping for mobile robots has been achieved with a large variety of methods. Among them, topological navigation using vision has the advantage of offering a scalable representation, and of relying on a common and affordable sensor. In previous work, we developed such an incremental and real-time topological mapping and localization solution, without using any metrical information, and by relying on a Bayesian visual loop-closure detection algorithm. In this paper, we propose an extension of this work by integrating metrical information from robot odometry in the topological map, so as to obtain a globally consistent environment model. Also, we demonstrate the performance of our system on the global localization task, where the robot has to determine its position in a map acquired beforehand. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ROBOT.2009.5152501 | ICRA |
Keywords | Field | DocType |
visual topological,mobile robot,real-time topological mapping,metrical information,localization solution,global localization task,topological navigation,previous work,visual localization,bayesian visual loop-closure detection,topological map,dictionaries,bayesian methods,simultaneous localization and mapping,mobile robots,visualization,navigation,machine vision,real time | Computer vision,Topology,Visualization,Odometry,Topological map,Artificial intelligence,Robot,Simultaneous localization and mapping,Mathematics,Mobile robot,Bayesian probability,Scalability | Conference |
Volume | Issue | ISSN |
2009 | 1 | 1050-4729 |
Citations | PageRank | References |
33 | 1.07 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrien Angeli | 1 | 291 | 11.87 |
| Stéphane Doncieux | 2 | 751 | 39.71 |
| Jean-Arcady Meyer | 3 | 870 | 102.62 |
| David Filliat | 4 | 646 | 47.26 |