SLAM and map merging

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Title: SLAM and map merging
Authors: León García, Ángel | Barea Navarro, Rafael | Bergasa Pascual, Luis Miguel | López Guillén, Elena | Ocaña Miguel, Manuel | Schleicher Gómez, David
Keywords: Multi-robot SLAM | Scan-matching | Fast-slam | Rao-blackwellised particle filter
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: Jan-2009
Publisher: Red de Agentes Físicos
Citation: LEÓN GARCÍA, Ángel, et al. “SLAM and map merging”. Journal of Physical Agents. Vol. 3, No. 1 (Jan. 2009). ISSN 1888-0258, pp. 13-23
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.
Sponsor: 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).
URI: |
ISSN: 1888-0258
DOI: 10.14198/JoPha.2009.3.1.03
Language: eng
Type: info:eu-repo/semantics/article
Peer Review: si
Appears in Collections:Revistas - JoPha - 2009, Vol. 3, No. 1

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