Simultaneous localization and mapping: A feature-based probabilistic approach

Piotr Skrzypczyński

doi:10.2478/v10006-009-0045-z

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Simultaneous localization and mapping: A feature-based probabilistic approach

International Journal of Applied Mathematics and Computer Science

Volume 19 (2009): Issue 4 (December 2009)

By: Piotr Skrzypczyński

Open Access

|Dec 2009

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.

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