Simultaneous Localization And Mapping: A feature-based probabilistic approach
Piotr Skrzypczyński
International Journal of Applied Mathematics and Computer Science, Tome 19 (2009), p. 575-588 / Harvested from The Polish Digital Mathematics Library

This article provides an introduction to Simultaneous Localization And Mapping (SLAM), with the focus on probabilistic SLAM utilizing a feature-based description of the environment. A probabilistic formulation of the SLAM problem is introduced, and a solution based on the Extended Kalman Filter (EKF-SLAM) is shown. Important issues of convergence, consistency, observability, data association and scaling in EKF-SLAM are discussed from both theoretical and practical points of view. Major extensions to the basic EKF-SLAM method and some recent advances in SLAM are also presented.

Publié le : 2009-01-01
EUDML-ID : urn:eudml:doc:207956
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Piotr Skrzypczyński. Simultaneous Localization And Mapping: A feature-based probabilistic approach. International Journal of Applied Mathematics and Computer Science, Tome 19 (2009) pp. 575-588. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv19i4p575bwm/

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