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Toward rich geometric map for SLAM: online detection of planets in 2D LIDAR
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.ORCID iD: 0000-0003-3011-1505
2013 (English)In: Journal of Automation, Mobile Robotics & Intelligent Systems, ISSN 1897-8649, E-ISSN 2080-2145, Vol. 7, no 1, 35-41 p.Article in journal (Refereed) Published
Abstract [en]

Rich geometric models of the environment are needed for robots to carry out their missions. However a robot operating in a large environment would require a compact representation. In this article, we present a method that relies on the idea that a plane appears as a line segment in a 2D scan, and that by tracking those lines frame after frame, it is possible to estimate the parameters of that plane. The method is divided in three steps: fitting line segments on the points of the 2D scan, tracking those line segments in consecutive scan and estimating the parameters with a graph based SLAM (Simultaneous Localisation And Mapping) algorithm.

Place, publisher, year, edition, pages
2013. Vol. 7, no 1, 35-41 p.
Keyword [en]
laser scanner, SLAM, LIDAR
National Category
Robotics
Identifiers
URN: urn:nbn:se:liu:diva-90553OAI: oai:DiVA.org:liu-90553DiVA: diva2:613758
Funder
eLLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2013-04-02 Created: 2013-04-02 Last updated: 2016-09-19

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Berger, Cyrille
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KPLAB - Knowledge Processing LabThe Institute of Technology
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