Predict Lab Student Projects

Bachelor project : Mini-segway racing

We regularly run student projects at the bachelor and master levels. We update the list of offered projects below before each term.

If you’re an EPFL team that would benefit from better control, please do contact us, as we do regularly run projects with a number of teams.

If you have a project in control or robotics that you’re excited about, please get in touch and we can try and make it work!

ALT

Motivation:

Although they might be optimal with respect to some mathematical objective, conventional controllers might not result in driving trajectories that are preferred or expected by human passengers. One approach for a different family of controllers is to train a Machine Learning model from human ‘expert’ demonstrations, such that the resulting controller seems to act similarly to a human driver.

Description:

In this project, we would like to learn a Neural Network controller from a large existing dataset of human-driven trajectories. This includes implementing a baseline Imitation Learning method first, and a more advanced method second. Arising challenges are typically related to the stability of the learnt controller and its behavior outside the training data distribution.

Ideally, after development in simulation, the project leads to the successful deployment of the controller on our ready-to-use real-world mini race car system.

Skills needed

– Strong background in Machine Learning and the relevant software tools (Python, PyTorch)

– Qualitative understanding of car dynamics or similar mobile robots

– Significant experience in coding projects

– Familiarity with ROS/ROS2 (Robot Operating System) is a plus

– Familiarity with C++ is a plus (for real-time deployment)

Comment
Directly contact [email protected] and [email protected] if interested.
Professor(s)
Colin Neil Jones (Laboratoire d’automatique 3), Johannes Christian Karl Waibel
Administration
Barbara Marie-Louise Frédérique Schenkel