Autonomous Racing with the Berkeley Autonomous Race Car
Francesco Borrelli, Professor
Mechanical Engineering
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
This project involves work on the perception, prediction, and control stacks of the 1/10th scale Berkeley Autonomous Race Car (BARC) platform. The goal is to perform multi-agent racing on an indoor track with onboard sensing and computation. Students can expect to learn about advanced modeling, planning, and control techniques in a high-performance racing setting.
Role: Students will develop the autonomy stack of and design experiments for an RC race car based platform. Specifically, we are looking for students who are experienced and interested in the areas of perception and state estimation, modeling and prediction of adversarial agents, data-driven system identification of dynamical systems, and learning-based control.
Qualifications: Students must be proficient in Python and/or C++ and have prior experience with the Robot Operating System (ROS).
We don't require that you be an expert in any area, but students must demonstrate a working knowledge of concepts in their area of interest.
Hours: 9-11 hrs
Mathematical and Physical Sciences Engineering, Design & Technologies