Título: SLAM and map merging
Autores: León García, Ángel
Barea Navarro, Rafael
Bergasa Pascual, Luis Miguel
López Guillén, Elena
Ocaña Miguel, Manuel
Schleicher Gómez, David
Fecha: 2009-11-23
2009-11-23
2009-01
Publicador: RUA Docencia
Fuente:
Tipo: info:eu-repo/semantics/article
Tema: Multi-robot SLAM
Scan-matching
Fast-slam
Rao-blackwellised particle filter
Ciencia de la Computación e Inteligencia Artificial
Descripción: This paper presents a multi-robot mapping and localization system. Learning maps and efficient exploration of an unknown environment is a fundamental problem in mobile robotics usually called SLAM (simultaneous localization and mapping problem). Our approach involves a team of mobile robots that uses Scan-Matching and Fast-SLAM techniques based on scan-laser and odometry information for mapping large environments. The single maps generated for each robot are more accurate than the maps generated only by odometry. When a robot detects another, it sends its processed map and the master robot generates a very accurate global map. This method cuts down the global map building time. Some experimental results and conclusions are presented.
Comunidad de Madrid and the University of Alcalá, support through the projects RoboCity2030 (CAM-S-0505/DPI/000176) and SLAM-MULEX (CCG07-UAH/DPI-1736).
Idioma: Inglés

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