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Paper details
Number 4 - December 2009
Volume 19 - 2009
Simultaneous localization and mapping: A feature-based probabilistic approach
Piotr Skrzypczyński
Abstract
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.
Keywords
mobile robot, navigation, simultaneous localization and mapping, feature matching