Name
Abstract | ||
|---|---|---|
In this paper the multi-robot localization problem is addressed. A new framework based on a spatially structured genetic algorithm
is proposed. Collaboration among robots is considered and is limited to the exchange of sensor data. Additionally, the relative
distance and orientation among robots are assumed to be available. The proposed framework (MR-SSGA) takes advantage of the
cooperation so that the perceptual capability of each robot is extended. Cooperation can be set-up at any time when robots
meet, it is fully decoupled and does not require robots to stop. Several simulations have been performed, either considering
cooperation activated or not, in order to emphasize the effectiveness of the collaboration strategy. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s11370-008-0025-4 | Intelligent Service Robotics |
Keywords | Field | DocType |
mobile robot · localization · genetic algorithms · complex networks,complex network,genetic algorithm | Robot localization,Computer vision,Computer science,Simulation,Complex network,Artificial intelligence,Robot,Genetic algorithm,Mobile robot,Distributed computing | Journal |
Volume | Issue | ISSN |
2 | 1 | 1861-2784 |
Citations | PageRank | References |
9 | 0.49 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Gasparri | 1 | 447 | 41.42 |
| Stefano Panzieri | 2 | 269 | 36.84 |
| Federica Pascucci | 3 | 106 | 15.62 |