{Treemap: An $O(log n)$ Algorithm for Simultaneous Localization and Mapping}
Type of publication: | Inproceedings |
Citation: | fre04c |
Booktitle: | {Spatial Cognition IV} |
Year: | 2005 |
Pages: | 455--476 |
Publisher: | Springer Verlag |
Note: | read the Autonomous Robots paper instead |
URL: | http://www.informatik.uni-brem... |
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. |
Userfields: | bdsk-url-1={http://www.informatik.uni-bremen.de/agebv/en/Treemap}, pdfurl={http://www.informatik.uni-bremen.de/agebv/downloads/published/fresesc04.pdf}, project={A1-RoboMap}, status={Reviewed}, |
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