Name
Abstract | ||
|---|---|---|
In this paper, we present a probabilistic analysis approach for analyzing market-based algorithms applied to the initial formation problem. These algorithms determine an assignment scheme for associating individual robots with goal positions necessary to achieve a desired formation while minimizing an objective function. The main contribution of this paper is a method that calculates the expected value of the objective function, which allows us to estimate and compare theoretically the performance of two task allocation algorithms. This probabilistic analysis is applied in different runtime scenarios. We validate our approach through both simulations and experiments with real robots. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1177/0278364909340333 | I. J. Robotic Res. |
Keywords | Field | DocType |
multi-robot teams,task allocation,probabilistic analysis. | Computer science,Algorithm,Probabilistic analysis of algorithms,Expected value,Artificial intelligence,Robot,Machine learning | Journal |
Volume | Issue | ISSN |
29 | 9 | 0278-3649 |
Citations | PageRank | References |
2 | 0.39 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antidio Viguria | 1 | 154 | 19.05 |
| Ayanna Howard | 2 | 558 | 82.43 |