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Giusti A.

Docente titolare del corso


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.


  1. Learn the fundamental problems, and their standard solutions, in autonomous mobile robotics and arm robotics.
  2. Gain hands-on experience in implementing algorithms for mobile robots using Python
  3. 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



Offerta formativa