Ressource pédagogique : 3.1. Examples for the Action in the EKF
In part 2, we have seen the
equations of the Bayes filter, which are the general
equations which allow us to update the probability
distribution, as the data from both proprioceptive sensors and
exteroceptive sensors are delivered.
We have seen a possible
implementation of these equations, based on...
cours / présentation - Date de création : 01-06-2015
Présentation de: 3.1. Examples for the Action in the EKF
Informations pratiques sur cette ressource
Anglais
Type pédagogique : cours / présentation
Niveau : master, master
Durée d'exécution : 9 minutes 14 secondes
Contenu : image en mouvement
Document : video/mp4
Taille : 338.67 Mo
Droits : libre de droits, gratuit
Droits réservés à l'éditeur et aux auteurs. This course material is provided under Creative Commons License BY-NC-ND: the name of the author should always be mentioned ; the user can exploit the work except in a commercial context and he cannot make changes to the original work.
Droits réservés à l'éditeur et aux auteurs. This course material is provided under Creative Commons License BY-NC-ND: the name of the author should always be mentioned ; the user can exploit the work except in a commercial context and he cannot make changes to the original work.
Description de la ressource pédagogique
Description (résumé)
In part 2, we have seen the equations of the Bayes filter, which are the general equations which allow us to update the probability distribution, as the data from both proprioceptive sensors and exteroceptive sensors are delivered. We have seen a possible implementation of these equations, based on a numerical solution: the grid localization. We have also started to see the equations of the Kalman filter, or better the extended Kalman filter. In part 3, we want to better explain these equations starting from a very simple example in 1D. Then we will consider problems like simultaneous localization mapping, and other theoretical issue about estimation. In this video, we start to discuss the first two equations of the Kalman filter.
"Domaine(s)" et indice(s) Dewey
- Applications. Automates (629.89)
- Génie informatique (621.39)
- Informatique - Traitement des données informatiques (004)
Thème(s)
AUTEUR(S)
-
Agostino Martinelli
EN SAVOIR PLUS
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Identifiant de la fiche
26417 -
Identifiant
oai:canal-u.fr:26417 -
Schéma de la métadonnée
- LOMv1.0
- LOMFRv1.0
- Voir la fiche XML
-
Entrepôt d'origine
Canal-u.fr
