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Two observer-based tracking algorithms for a unicycle mobile robot

100%

Jakubiak J., Lefeber E., Tchoń K., Nijmeijer H.

International Journal of Applied Mathematics and Computer Science

2002

tom 12

nr 4

513-522

A trajectory tracking problem for the three-dimensional kinematic model of a unicycle-type mobile robot is considered. It is assumed that only two of the tracking error coordinates are measurable. By means of cascaded systems theory we develop observers for each of the error coordinates and show the K-exponential convergence of the tracking error in combined closed-loop observer-controller systems. The results are illustrated with computer simulations.

Simultaneous Localization And Mapping: A feature-based probabilistic approach

100%

Skrzypczyński P.

International Journal of Applied Mathematics and Computer Science

2009

tom 19

nr 4

575-588

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.

Ograniczanie wyników

2 International Journal of Applied Mathematics and Computer Science

1 Jakubiak J.

1 Lefeber E.

1 Nijmeijer H.

1 Skrzypczyński P.

1 Tchoń K.

1 2009

1 2002

Wyniki wyszukiwania

Two observer-based tracking algorithms for a unicycle mobile robot

Simultaneous Localization And Mapping: A feature-based probabilistic approach