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Publication type: Technical Report
Author: U. Frese
Title: Treemap: An $O(log n)$ Algorithm for Indoor Simultaneous Localization and Mapping
Number: 006-03/2006
Year published: 2006
Institution: Universität Bremen, SFB/TR 8 Spatial Cognition
Abstract: This article presents a very efficient SLAM algorithm that works by hierarchically dividing a 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. To keep those matrices small, only those landmarks are represented that are 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 full least-square estimate for that region is computed in only $O(k^3 log n)$ computation time for $n$ landmarks. A global least square estimate needs $O(kn)$ computation time with a very small constant (12.37ms for n=11300). Furthermore, the proposed hierarchy allows the rotation of individual regions to reduce linearization errors.

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.sfbtr8.uni-bremen.de/papers/SFB_TR8Rep006-03_2006.pdf
Keywords: SLAM treemap localization mapping
Note / Comment: Companion report to the Autonomous Robots article with the same title.
Status: Other
Last updated: 28. 10. 2008

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