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SLAM and Map Merging

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Author(s): Luis Miguel Bergasa Pascual | Angel Leon | Rafael Barea | Elena Lopez | Manuel Ocaña

Journal: Journal of Physical Agents
ISSN 1888-0258

Volume: 3;
Issue: 1;
Start page: 13;
Date: 2009;
Original page

Keywords: Multi-robot SLAM | scan-mathcing | fast-slam | rao-blackwellised particle filter.

ABSTRACT
This paper presents a multi-robot mapping and localization system. Learning maps and efficient exploration of unknown environment is a fundamental problem in mobile robotics usually called SLAM (simultaneous localization and mapping problem). Our approach uses a team of mobile robots which uses scan-matching and fast-slam techniques for mapping. The single maps generates for each robot are more accurate than map generated by odometry data. When a robot detects another, send its processed map and the master robot can generates a global map very accurate. This way, time necessary to built the global map is reduced.
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