Robotics
Persone
Descrizione
The course theory part explores the following topics:
- 2D and 3D pose representation and transformations
- Workspace, C-Space, Degrees of Freedom
- Kinematics for arms and wheeled robots
- Feedback-based control
- Sensors
- Localization, Mapping, SLAM
- Path planning
The practical part explores algorithm implementations with Jupyter Notebooks and ROS.
Good Python programming skills are required for assignments and project work.
Obiettivi
- Learn the fundamental problems, and their standard solutions, in autonomous mobile robotics and arm robotics.
- Gain hands-on experience in implementing algorithms for mobile robots using Python
- Learn to use ROS, a powerful ecosystem for robotics
Modalità di insegnamento
In presenza
Impostazione pedagogico-didattica
- Implementing algorithms and solving exercises
- Studying theory topics
- Hands-on projects
Modalità d’esame
- 50% theory (written exam)
- 50% labs and assignments
Bibliografia
Approfondimento
- Ben-Ari, Mordechai, Mondada, Francesco. Elements of Robotics. Springer Open, 2017. (https://link.springer.com/book/10.1007/978-3-319-62533-1)
- Siegwart, Roland, Nourbakhsh, Illah Reza, Scaramuzza, Davide. Introduction to autonomous mobile robots. 2nd ed.. Cambridge, MA: MIT Press, 2011. (http://www.mobilerobots.ethz.ch/)
Offerta formativa
- Master of Science in Artificial Intelligence, Lezione e laboratorio, 1° anno
- Master of Science in Computational Science, Lezione e laboratorio, A scelta, 1° anno
- Master of Science in Informatics, Lezione e laboratorio, Artificial Intelligence, A scelta, 1° anno
- Master of Science in Informatics, Lezione e laboratorio, Geometric and Visual Computing, A scelta, 2° anno
- Master of Science in Management and Informatics, Lezione e laboratorio, A scelta, 1° anno
- Master of Science in Management and Informatics, Lezione e laboratorio, A scelta, 2° anno
- Dottorato in Scienze informatiche, Lezione e laboratorio, A scelta, 1° anno (4 ECTS)
