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Robotics

Description

COURSE OBJECTIVES

  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

 

COURSE DESCRIPTION

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 implementation with Jupyter Notebooks (good programming skills with Python are required) and ROS.

 

LEARNING METHODS

  • Implementing algorithms and solving exercises
  • Studying theory topics
  • Hands-on projects

 

EXAMINATION INFORMATION

  • 50% theory (written exam)
  • 50% labs and assignments

 

REFERENCES

  • Course slides - Jupyter notebooks at https://github.com/alessandro-giusti/teaching-notebooks/tree/master/robotics

Where required, some textbook chapters:

  • Introduction to Autonomous Mobile Robots, Second Edition (Roland Siegwart, Illah Reza Nourbakhsh and Davide Scaramuzza)
  • Elements of Robotics (available online): https://link.springer.com/book/10.1007/978-3-319-62533-1

People

 

Giusti A.

Course director

Additional information

Semester
Spring
Academic year
2021-2022
ECTS
6
Language
English
Education
Master of Science in Artificial Intelligence, Foundation course, 1st year
Master of Science in Informatics, Elective course, 1st year
Master of Science in Informatics, Elective course, 2nd year
Master of Science in Management and Informatics, Elective course, Lecture, 1st year
Master of Science in Management and Informatics, Elective course, 2nd year