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AROBOTS
2006

Treemap: An O(log n) algorithm for indoor simultaneous localization and mapping

9 years 10 months ago
Treemap: An O(log n) algorithm for indoor simultaneous localization and mapping
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(k2 ) 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(k3 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). The algorithm is evaluated for map quality, storage space and computation time using simulated and real experiments in an office environment.
Udo Frese
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2006
Where AROBOTS
Authors Udo Frese
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