| Título: | Voronoi-based space partitioning for coordinated multi-robot exploration |
| Autores: |
Wu, Ling García García, Miguel Ángel Puig Valls, Domenec Solé Ribalta, Albert |
| Fecha: |
2009-11-23 2009-11-23 2007-09 |
| Publicador: | RUA Docencia |
| Fuente: |
 |
| Tipo: | info:eu-repo/semantics/article |
| Tema: |
Multi-robot Exploration Polygonal model K-means Ciencia de la Computación e Inteligencia Artificial |
| Descripción: |
Recent multi-robot exploration algorithms usually rely on occupancy grids as their core world representation. However, those grids are not appropriate for environments that are very large or whose boundaries are not well delimited from the beginning of the exploration. In contrast, polygonal representations do not have such limitations. Previously, the authors have proposed a new exploration algorithm based on partitioning unknown space into as many regions as available robots by applying K-Means clustering to an occupancy grid representation, and have shown that this approach leads to higher robot dispersion than other approaches, which is potentially beneficial for quick coverage of wide areas. In this paper, the original K-Means clustering applied over grid cells, which is the most expensive stage of the aforementioned exploration algorithm, is substituted for a Voronoi-based partitioning algorithm applied to polygons. The computational cost of the exploration algorithm is thus significantly reduced for large maps. An empirical evaluation and comparison of both partitioning approaches is presented. This work is partially supported by the Government of Spain under MCYT DPI2004-07993-C03-03. Ling Wu is supported by a FPI scholarship from the Spanish Ministry of Education and Science. |
| Idioma: | Inglés |
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