SLAM and map merging

• Autores: Angel León García, Rafael Barea Navarro, Luis M. Bergasa Pascual, María Elena López Guillén, Manuel Ocaña Miguel, David Schleicher Gómez
• Localización: JoPha: Journal of Physical Agents, ISSN-e 1888-0258, Vol. 3, Nº. 1, 2009, págs. 13-23
• Idioma: inglés
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• Resumen

  • 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.