SLAM and map merging

1. Ángel León García
2. Rafael Barea Navarro
3. Luis Miguel Bergasa Pascual
4. Elena López Guillén
5. Ocaña Miguel, Manuel
6. David Schleicher Gómez

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DOI: 10.14198/JOPHA.2009.3.1.03 DIALNET GOOGLE SCHOLAR lock_openRUA editor

More publications in: JoPha: Journal of Physical Agents

Abstract

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.

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