Name
Abstract | ||
|---|---|---|
In this paper, a novel genetic algorithm based on a “collaborative” fitness-sharing technique to deal with the multi-robot
localization problem is proposed. Indeed, the use of the fitness-sharing is twofold and competitive. It preserves the diversity
among individuals during the space exploration process, thus maintaining evolutionary niches over time, and reinforces the
best hypotheses by means of collaboration among robots, thus augmenting the selection pressure. Simulations by exploiting
the robotics framework Player/Stage have been performed along with a proper statistical analysis for performance assessment. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s11370-010-0065-4 | Intelligent Service Robotics |
Keywords | Field | DocType |
multi-robot · localization · genetic algorithm,genetic algorithm,statistical analysis | Robot localization,Simulation,Computer science,Fitness sharing,Space exploration,Artificial intelligence,Robot,Robotics,Genetic algorithm,Machine learning,Statistical analysis | Journal |
Volume | Issue | ISSN |
3 | 3 | 1861-2784 |
Citations | PageRank | References |
1 | 0.38 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Gasparri | 1 | 447 | 41.42 |
| Stefano Panzieri | 2 | 269 | 36.84 |
| Attilio Priolo | 3 | 36 | 4.78 |