Search for: [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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