Montreal Robotics Summer School 

The Montreal Robotics Summer School offers tutorials and lectures on state-of-the-art machine learning methods for training the next generation of learning robots. The summer school is an extension supported by the many robotics groups around Montreal. 

The summer school will take place at Mila, the Quebec AI Institute, the largest academic organization for deep learning researchers worldwide. Attendees will have the opportunity to learn about current deep reinforcement learning methods, how to apply them to real hardware, sim2real transfer techniques, and experience with legged robotics.

The Content

The goal of the summer school is to provide a crash course in how to control and program autonomous robots. 

Some of the topics we cover include:

• State estimation

• Deep learning and computer vision for robot perception

• Robot manipulation

• SLAM

• Planning and planning with learned models

• Foundational models for robot control

• Reinforcement learning and sim2real transfer

Attendees also get the chance to test their code on real robot hardware.

The content assumes a strong knowledge of Python programming, with some Linux and hardware skills.

Challenge: On the last day of the summer school, teams will use their new skills to compete in designing the best vision-based navigation controller on a quadruped robot to navigate an obstacle course.

You can see a summary of last year's school here.

Speakers

Organizers

• Glen Berseth

• Christopher Yee Wong

• Pierre-Yves Lajoie

• Kirsty Ellis

• Nicolas Fleury-Rousseau

• Soma Karthik

• Simon Roy

• Maëva Guerrier

• Olivier Lessard

Sponsors

The Montreal Robotics Summer School is indebted to our generous partners (coming soon)