Temat: Simultaneous Localization and Mapping - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Simultaneous localization and mapping: A feature-based probabilistic approach
Autorzy:: Skrzypczyński, P.
Powiązania:: https://bibliotekanauki.pl/articles/929972.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: robot mobilny
lokalizacja równoczesna
dopasowanie właściwości
mobile robot
simultaneous localization and mapping
feature matching
Opis:: 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.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2009, 19, 4; 575-588
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Straight-lines modelling using planar information for monocular SLAM
Autorzy:: Santana, A. M.
Medeiros, A. A. D.
Powiązania:: https://bibliotekanauki.pl/articles/331312.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: SLAM
filtr Kalmana
transformata Hough'a
Simultaneous Localization and Mapping (SLAM)
Kalman filter
Hough transform
monocular vision
Opis:: This work proposes a SLAM (Simultaneous Localization And Mapping) solution based on an Extended Kalman Filter (EKF) in order to enable a robot to navigate along the environment using information from odometry and pre-existing lines on the floor. These lines are recognized by a Hough transform and are mapped into world measurements using a homography matrix. The prediction phase of the EKF is developed using an odometry model of the robot, and the updating makes use of the line parameters in Kalman equations without any intermediate stage for calculating the distance or the position. We show two experiments (indoor and outdoor) dealing with a real robot in order to validate the project.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2012, 22, 2; 409-421
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

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