Simultaneous localization and mapping: A feature-based probabilistic approach
[ 1 ] Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | [ P ] employee
2009
scientific article
english
- mobile robot
- navigation
- simultaneous localization and mapping
- feature matching
EN 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.
575 - 588
CC BY-NC-ND (attribution - noncommercial - no derivatives)
open journal
final published version
public
0,684