Master in Artificial Intelligence and Robotics

Elective in Artificial Intelligence

Proff. Giuseppe De Giacomo, Luigi Freda, Luca Iocchi, Fiora Pirri

A.Y. 2017/2018

Description of the course

The course gives 12 credits and is structured in the four modules described in the right frame. Please refer to each of the modules, following the links in this page for additional details.

Professor in charge of the registration for A.Y. 2017/18 is
Prof. Luca Iocchi.

IMPORTANT Any request for change of a module must be authorized by the professor in charge for the A.Y. (see above) before attending the class and giving the exam of the module involved in the change.
An e-mail should be sent to ask for a change (including detailed motivations for the change). Notification about acceptance/rejection of the change will be communicated soon after receiving the e-mail.

VERY IMPORTANT Since January 2018, exams with including unauthorized changes of the modules will not be registered. If you are unsure about your status, please contact the professor in charge for the A.Y. (see above) as soon as possible.


Lectures will be given in the second semester (26/2/2018 - 1/6/2018) with the following schedule:

26/2 - 13/4/2018 
Reasoning Robots              Tue 14-16, Fri 14-17
Human Robot Interaction   Wed 11-13, Thu 11-13, Fri 17-18

16/4 - 1/6/2018 

3D Dynamic Reconstruction from Video and
Introduction to Pattern Recognition


Each module has specific modalities and dates.
Please check the module web-sites.

After completing all the modules, contact the Professor in charge of the registration providing the following information:
name, matricola, list of given exams (title of the module, professor of the module, and grade).

Reasoning Robots:

Reasoning about Actions in Cognitive Robotics

Prof. Giuseppe De Giacomo
Prof. Luca Iocchi

3 Credits - II Semester

The development of intelligent robots is one of the most important goals of Artificial Intelligence and Robotics. In this course we will present different enabling techniques to realize this goal, focussing in particular on advanced forms of automated behaviour synthesis based on temporal logics and action theories
in both deterministic and non-deterministic settings.
Moreover, we will give the students the opportunity to integrate such high-level forms of reasoning with state-of-the-art probabilistic robotics, computer vision, and machine learning tools.

3D Dynamic Reconstruction from Video

Prof. Luigi Freda

3 Credits - II Semester

Today, commodity imaging devices are used extensively in Robotics since they are lightweight, low-cost and able to provide very rich information. In fact, these sensors enable robots to reliably interact with their surrounding environment by giving them the possibility to build a 3D dynamic and dense reconstruction of the scene. Indeed, such a 3D reconstruction can be used by a robot at different levels and allows, for instance, safe navigation, accurate object grasping and manipulation, tracking of dynamic objects, semantic understanding, etc. 
In this course, we will learn how to:
- compute a 3D reconstruction from imaging sensors 
- maintain a 3D dynamic representation of scenes where objects may move
- apply a basic segmentation to the obtained model 
- put our hands on some of the most advanced open source 3D reconstruction SDKs in order to customize and adapt them to our needs. 
The course presents techniques and tools which have many potential applications, including mixed-reality and virtual reality.

Prof. Luca Iocchi
Prof. Mary Ellen Foster (Univ. of Glasgow)

3 Credits - II Semester

Applications involving robots interacting with people are gaining increasing interest. The course will provide an overview of recent methods and techniques for Human-Robot Interaction and Social Robotics. Several interaction modalities will be discussed in the course, including: vision, speech, body motion, user interfaces, etc.

Prof. Fiora Pirri

3 Credits - II Semester