-
- Label UNT : UNIT
-
- Date de réalisation : 1 Juin 2015
- Durée du programme : 9 min
- Classification Dewey : Applications. Automates, Génie informatique, Informatique - Traitement des données informatiques
-
- Catégorie : Vidéocours
- Niveau : niveau Master (LMD), 2ieme cycle
- Disciplines : Informatique, Informatique
- Collections : 2. Bayes and Kalman Filters
- ficheLom : Voir la fiche LOM
-
- Langue : Anglais
- Mots-clés : robotics, autonomous vehicles, informatics, mobile robots
- Conditions d’utilisation / Copyright : 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.
2.2. Characterization of proprioceptive and exteroceptive sensors
Before deriving the
equations of the Bayes filter, I want to remind you a few concepts
in the theory of probability, and also some
mathematical characterization for the statistical
error of the robot's sensors.
In particular, in this
sequence, what I want to do, is to derive the link between
the robot configuration, and the physical quantities that
are measured by the robot's sensors.
commentaires
Ajouter un commentaire Lire les commentaires