15 résultats : MARTINELLI AGOSTINO

Attention : l'accès aux ressources peut être restreint, soit pour des raisons juridiques, soit par la volonté de l'auteur.
15 résultats
page 1 sur 2
résultats 1 à 10
Canal-U
?2.1. Localization process in a probabilistic framework: basic concepts
Description : In this part, we will talk about localization which is a fundamental problem that a robot has to be able to solve in order to accomplish almost any tasks. In particular, we will start by discussing several motion sensor models and, starting from them, we will derive and we will discuss the most ...
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
?2.1. Localization process in a probabilistic framework: basic concepts
 Ajouter à mon panier
Accéder aux documents
Canal-U
2.3. Wheel encoders for a differential drive vehicle
Description : In this video, we want to discuss the case of a wheel encoders in 2D, and in particular the case of a robot equipped with a differential drive which is very popular in mobile robotics.
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
2.3. Wheel encoders for a differential drive vehicle
 Ajouter à mon panier
Accéder aux documents
Canal-U
2.4. Sensor statistical models
Description : So far in the characterization of our sensor measurements, we didn't talk about the errors. This is precisely what we want to do in this video. In particular, we want to compute two probability distributions which are these: P of having an exteroceptive measurement Z by knowing the state, so the ...
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
2.4. Sensor statistical models
 Ajouter à mon panier
Accéder aux documents
Canal-U
2.7. Grid Localization: an example in 1D
Description : Now that we have the equations of the Bayes filter, we need a method in order to implement in real cases these equations. So, in the following, I want to discuss two methods, which are commonly adopted by the Mobile Robotics Community and, these, if you want, correspond to two extreme solutions ...
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
2.7. Grid Localization: an example in 1D
 Ajouter à mon panier
Accéder aux documents
Canal-U
2.5. Reminds on probability
Description : In this sequence I want to remind you a few concepts in the theory of probability and then in the next one we finally derive the equations of the Bayes filter. So the concept that I want to remind you are 3: the Markov assumption, the theorem of a total probability and the Bayes theorem.
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
2.5. Reminds on probability
 Ajouter à mon panier
Accéder aux documents
Canal-U
2.8. The Extended Kalman Filter (EKF)
Description : We have seen the grid localization, and the advantage of this approach is that we can deal with any kind of probability distribution; in particular we don't need to do a Gaussian assumption. The drawback is that the solution becomes very expensive. There exists another solution that is the Kalman ...
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
2.8. The Extended Kalman Filter (EKF)
 Ajouter à mon panier
Accéder aux documents
Canal-U
2.6. The Bayes Filter
Description : The equations of the Bayes filters are the equation that allow us to update the probability distribution for the robot to be in a given configuration by integrating the information that are in the measurements provided by the robot.
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
2.6. The Bayes Filter
 Ajouter à mon panier
Accéder aux documents
Canal-U
3.1. Examples for the Action in the EKF
Description : 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 ...
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
3.1. Examples for the Action in the EKF
 Ajouter à mon panier
Accéder aux documents
Canal-U
3.2. Examples for the Perception in the EKF
Description : In this video we discuss the second two equations of the Kalman filter.
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
3.2. Examples for the Perception in the EKF
 Ajouter à mon panier
Accéder aux documents
Canal-U
3.3. The EKF is a weight mean
Description : In this video I want to discuss the second two equations of the Kalman filter. And in particular I want to show that these actually perform a kind of weight mean.
Mots clés : robotics, autonomous vehicles, informatics, mobile robots
Date : 01-06-2015
Droits : 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.
 En savoir plus
 Description complète
3.3. The EKF is a weight mean
 Ajouter à mon panier
Accéder aux documents