I'm a member of the Paris artificial intelligence research institute (PRAIRIE-PSAI). Below are the teaching materials for classes I'm teaching at École Normale Supérieure, Master MVA and Mines de Paris.
Lectures ¶
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Modeling and control of legged locomotion
Stéphane Caron. Fall class at École normale supérieure, Paris.
The objective of this lecture is to understand the physics of balancing and how we can leverage them to design locomotion controllers.
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Reinforcement learning for legged robots
Stéphane Caron. Fall class at École normale supérieure, Master MVA and Mines de Paris.
This is a crash course on applying reinforcement learning to train policies that balance real legged robots. We first review the necessary basics: partially-observable Markov decision processes, value functions, the goal of reinforcement learning. We then focus on policy optimization: REINFORCE, policy gradient and proximal policy optimization (PPO). We finally focus on techniques to train real-robot policies from simulation data: domain randomization, simulation augmentation, teacher-student distillation, reward shaping, ...
Courses ¶
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Robotics - Master MVA - Fall 2025
Silvère Bonnabel, Stéphane Caron, Justin Carpentier, Ajay Sathya and Pierre-Brice Wieber. Fall 2025 course at Master MVA, Paris.
A large part of the recent progress in robotics has sided with advances in machine learning, optimization and computer vision. The objective of this course is to introduce the general conceptual tools behind these advances and show how they have enabled robots to perceive the world and perform tasks ranging, beyond factory automation, to highly-dynamic saltos or mountain hikes. The course covers modeling and simulation of robotic systems, motion planning, inverse problems for motion control, optimal control, and reinforcement learning. It also includes practical exercises with state-of-the-art robotics libraries, and a broader reflection on our responsibilities when it comes to doing research and innovation in robotics.
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Robotics - Master MVA - Fall 2024
Silvère Bonnabel, Stéphane Caron, Justin Carpentier, Ajay Sathya and Pierre-Brice Wieber. Fall 2024 course at Master MVA, Paris.
A large part of the recent progress in robotics has sided with advances in machine learning, optimization and computer vision. The objective of this course is to introduce the general conceptual tools behind these advances and show how they have enabled robots to perceive the world and perform tasks ranging, beyond factory automation, to highly-dynamic saltos or mountain hikes. The course covers modeling and simulation of robotic systems, motion planning, inverse problems for motion control, optimal control, and reinforcement learning. It also includes practical exercises with state-of-the-art robotics libraries, and a broader reflection on our responsibilities when it comes to doing research and innovation in robotics.
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Robotics - Master MVA - Fall 2023
Silvère Bonnabel, Stéphane Caron, Justin Carpentier and Pierre-Brice Wieber. Fall 2023 course at Master MVA, Paris.
A large part of the recent progress in robotics has sided with advances in machine learning, optimization and computer vision. The objective of this lecture is to introduce the general conceptual tools behind these advances and show how they have enabled robots to perceive the world and perform tasks ranging, beyond factory automation, to highly-dynamic saltos or mountain hikes. The course covers modeling and simulation of robotic systems, motion planning, inverse problems for motion control, optimal control, and reinforcement learning. It also includes practical exercises with state-of-the-art robotics libraries, and a broader reflection on our responsibilities when it comes to doing research and innovation in robotics.