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Publication type: Article in Proceedings
Author: U. Frese
Editor: C. Freksa
Title: Treemap: An $O(log n)$ Algorithm for Simultaneous Localization and Mapping
Book / Collection title: Spatial Cognition IV
Page(s): 455 – 476
Year published: 2005
Publisher: Springer Verlag
Abstract: This paper presents a very efficient SLAM algorithm that works by hierarchically dividing the map into local regions and subregions. At each level of the hierarchy each region stores a matrix representing some of the landmarks contained in this region. For keeping the matrices small only those landmarks are represented being observable from outside the region.

A measurement is integrated into a local subregion using $O(k^2)$ computation time for $k$ landmarks in a subregion. When the robot moves to a different subregion a global update is necessary requiring only $O(k^3 log n)$ computation time for $n$ overall landmarks.

The algorithm is evaluated for map quality, storage space and computation time using simulated and real experiments in an office environment.
Internet: http://www.informatik.uni-bremen.de/agebv/en/Treemap
PDF Version: http://www.informatik.uni-bremen.de/agebv/downloads/published/fresesc04.pdf
Note / Comment: read the Autonomous Robots paper instead
Status: Reviewed
Last updated: 27. 03. 2009

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