Name
Abstract | ||
|---|---|---|
We consider a scenario where the aim of a group of agents is to perform the optimal coverage of a region according to a sensory function. In particular, centroidal Voronoi partitions have to be computed. The difficulty of the task is that the sensory function is unknown and has to be reconstructed on line from noisy measurements. Hence, estimation and coverage needs to be performed at the same time. We cast the problem in a Bayesian regression framework, where the sensory function is seen as a Gaussian random field. Then, we design a set of control inputs which try to find a good balance between coverage and estimation, also discussing convergence properties of the algorithm. Numerical experiments show the effectiveness of the new approach. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ECC.2015.7330912 | 2015 EUROPEAN CONTROL CONFERENCE (ECC) |
Keywords | Field | DocType |
estimation,base stations | Convergence (routing),Mathematical optimization,Gaussian random field,Regression,Computer science,Bayesian linear regression,Gaussian,Coverage control,Voronoi diagram | Journal |
Volume | Citations | PageRank |
abs/1407.5807 | 2 | 0.37 |
References | Authors | |
10 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Carron | 1 | 2 | 0.37 |
| Marco Todescato | 2 | 27 | 6.63 |
| Ruggero Carli | 3 | 894 | 69.17 |
| Luca Schenato | 4 | 1188 | 94.99 |
| Pillonetto Gianluigi | 5 | 877 | 80.84 |