Information-theoretic environment modeling for efficient topological localization
Rady, Sherine; Badreddin, Essam;
Abstract
Place recognition is a vital methodology for modeling environments and localizing autonomous mobile robots topologically. It can also be integrated in a hierarchical framework where it guides a fast and more precise metric position estimation. Especially for those hierarchical frameworks, it is crucial that the place recognition modules be highly accurate. In this paper, an information-theoretic approach that focuses on the efficiency of place recognition for topological environment modeling and localization is presented. The approach relies on a minimal discriminative feature set obtained from an entropy-based qualitative evaluation and a codebook compression. The generated environment feature map achieves a significant combination of high localization accuracy, speed and less memory storage. © 2010 IEEE.
Other data
Title | Information-theoretic environment modeling for efficient topological localization | Authors | Rady, Sherine ; Badreddin, Essam | Keywords | Codebook;Environment modeling;Feature compression;Feature evaluation;Information theory;Map building;Place recognition;Topological localization | Issue Date | 1-Dec-2010 | Conference | Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10 | ISBN | 9781424481354 | DOI | 10.1109/ISDA.2010.5687050 | Scopus ID | 2-s2.0-79851474010 |
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