Robotics – Master MVA
Welcome to the web page for the robotics class of the MVA master's program, taught by Justin Carpentier, Stéphane Caron, Silvère Bonnabel, Pierre-Brice Wieber and Ajay Sathya (TA).
A large part of the recent progress in robotics has sided with advances in machine learning, optimization and computer vision. The objective of this class 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.
- Assignment:
0_introduction_to_numerical_robotics.ipynb- Due on 2024-10-16, 23:59 CEST
- Humanoids 2024 conference: check out the procedure on this page (cover letter)
- Mailing list:
robotics-mva24@inria.fr(subscribe) - Research internships:
robotics-mva24-internships@inria.fr(subscribe)
Next lectures
Lectures take place on Thursdays from 9:00 AM CET to 12:00 PM CET.
| Date | Where | Topic | Teacher | TA |
|---|---|---|---|---|
| 17/10/24 | ENS Ulm | Motion planning | Stéphane Caron | Ajay Sathya |
| 24/10/24 | ENS Ulm | Inverse kinematics | Justin Carpentier | Ajay Sathya |
| 31/10/24 | ENS Ulm | - | - | - |
| 07/11/24 | ENS Ulm | Responsible robotics | Pierre-Brice Wieber | Ajay Sathya |
| 14/11/24 | ENS Ulm | Reinforcement learning for legged robots | Stéphane Caron | Ajay Sathya |
| 21/11/24 | ENS Ulm | Perception and estimation | Silvère Bonnabel | - |
| 28/11/24 | ENS Ulm | Optimal control and simulation | Justin Carpentier | Ajay Sathya |
| 05/12/24 | Inria Paris | Final poster session | All | - |
- ENS Ulm is located 45 rue d'Ulm, 75005 Paris. Lectures take place in the Galois amphitheatre.
- Inria Paris is located 48 rue Barrault, 75013 Paris.
Materials
1. Introduction to robotics
This first lecture is a general introduction of modeling robotic systems. We review basic notions of control theory to describe the evolution of dynamical systems and introduce standard robot dynamics concepts.
Contents:
Topics:
- What is robotics?
- Dynamical systems
2. Kinematics
Robotics is about producing motion. We now dive into the mathematical representation of robots (articulated systems of rigid bodies) and their motions (relative transforms and generalized velocities of these rigid bodies).
Contents:
Topics:
- Rotations: SO(3)
- Angular velocities: so(3)
- Rigid-body transforms: SE(3)
- Rigid-body velocities: se(3)
Related MVA courses:
- Géometrie et espaces de formes: differentiable geometry, Lie groups
References:
- Modern Robotics: Mechanics, Planning, and Control, Lynch and Park (2017).
- A mathematical introduction to robotic manipulation, Murray, Li and Sastry (2017).
- An introduction to optimization on smooth manifolds, Boumal (2023).
Evaluation
Evaluation for this class will be based on weekly homework (20%) and either a project or an article study (80%).
Homework
Homework topics will be handed out and started in tutorial (TP) sessions. Lecturers will help get everyone started during those sessions, then the tutorials can be finished as homework. Tutorials are due on the Wednesday (Paris time) preceding the next lecture. They can all be found in the robotics-mva-2024 repository on GiHub.
To return your solution:
- Export your notebook to HTML from JupyterLab:
File→Save and Export Notebook As...→HTML - Make sure your export includes all cell outputs (don't clear cells before exporting)
- Send it to Ajay Sathya by e-mail
Final evaluation
Final evaluation consists in either a project or an artical study, carried out by pairs of students (i.e. groups of size 2):
In projects, students select a topic of interest. A base list of topics will be proposed, ranging from well-known to cutting-edge research works. Students can pick/adapt from this list, or come up with their own proposals (e.g. build their own robots for a custom task, and implement its perception and action using some of the methods studied during the course).
In article studies, students read and report on a research paper from the list in the evaluation topics document. We strongly encourage a dash of creativity: students should be critical of the works they read, try to reproduce them (e.g. in simulation) to identify shortcomings or limitations of the assumptions made in the paper, and try to propose some next steps to overcome those. Examples of next steps include extending a proof, implementing another feature, trying the solution in a different context, etc.
Deliverables are a small report and a poster, to be presented to teachers, TAs and other students at the Final poster session on December 5th (see the calendar above).