Robotics

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