Name
Abstract | ||
|---|---|---|
This paper describes the design and testing of a system to enable large scale cooperative navigation of autonomous vehicles moving on a priori unknown routes in changing environments. A large-scale learning-mapping approach and a replay-localization method are combined to achieve cooperative navigation. The mapping approach is based on a proposed hierarchical/hybrid BiCam SLAM approach-global level and local maps-, which will be generalized to be executed on multiple vehicles moving as a convoy. A global 3D map maintains the relationships between a series of local submaps built by the first vehicle of the convoy (leader), defining a path that all other vehicles (followers) must stay on. Only single camera setups are considered. The overall approach is evaluated with real data acquired in an urban environment. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICECS.2011.6122364 | Electronics, Circuits and Systems |
Keywords | DocType | ISBN |
SLAM (robots),learning (artificial intelligence),autonomous vehicle navigation,changing environment,hierarchical BiCam SLAM approach,hybrid BiCam SLAM approach,unknown environment,vehicle communication,visual navigation | Conference | 978-1-4577-1844-1 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David A. Marquez-Gamez | 1 | 0 | 0.34 |
| Michel Devy | 2 | 542 | 71.47 |