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.
robotics-mva24@inria.fr (subscribe)robotics-mva24-internships@inria.fr (subscribe)Lectures take place on Thursdays from 9:00 AM CET to 12:00 PM CET.
| Date | Where | Topic | Teacher | TA |
|---|---|---|---|---|
| 03/10/24 | Inria Paris | Introduction to robotics | Justin Carpentier | - |
| 10/10/24 | Inria Paris | Configuration space, rigid transforms | Stéphane Caron | Ajay Sathya |
| 17/10/24 | Inria Paris | Motion planning | Stéphane Caron | Ajay Sathya |
| 24/10/24 | Inria Paris | Inverse kinematics | Stéphane Caron | Ajay Sathya |
| 31/10/24 | Inria Paris | Perception and estimation | Silvère Bonnabel | - |
| 07/11/24 | Inria Paris | Optimal control and simulation | Justin Carpentier | Ajay Sathya |
| 14/11/24 | TBD | Reinforcement learning for legged robots | Stéphane Caron | Ajay Sathya |
| 28/11/24 | Inria Paris | Responsible robotics | Pierre-Brice Wieber | Ajay Sathya |
| 05/12/24 | Inria Paris | Final poster session | All | - |
Inria Paris is located 48 rue Barrault, 75013 Paris. Lectures take place in the Jacques-Louis Lions amphitheatre, to the right when entering the lobby.
Evaluation for this class will be based on weekly homework (20%) and either a project or an article study (80%).
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:
File → Save and Export Notebook As... → HTMLFinal 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 7th (see the calendar for details).