Robot Open Autonomous Racing (ROAR™)

Led by its faculty members with deep expertise in AI and autonomous driving, Berkeley is proud to announce and host a new AI racecar competition in 2020. The Robot Open Autonomous Racing (ROAR) competition will pit multiple student racing teams to compete for speed and vehicle skills at the heart of the iconic Berkeley campus. 
 
The participating teams will adopt the set of common 1/10 RC car hardware as regulated by a rules committee. The regulations aim to ensure the competition to be affordable and fair to our target students. Different teams are allowed to upgrade their car hardware as permitted by the regulation and to develop and deploy their own autonomous driving software.
 
In order to preserve the safety and well-being of all students and members in our community, the decision has been made to host a virtual debut competition for ROAR in Fall 2020.

Steering Committee:

Francesco Borrelli
Faculty
Shankar Sastry
Faculty
Koushil Sreenath
Faculty
Allen Yang
Faculty

Virtual Competition Date:

Saturday, December 12, 2020

Agenda and more information to be released soon.

Leagues:

Autonomous Vehicle competition with two game formats – Human-Driver format and a fully autonomous driving format.

Track Standard and Localization Library

Please download the following files for information on Localization Module

1. Product Requirement Documentation for the ROAR SLAM System

2. AR Set-up and Marker Library Package

3. Python Localization Library Package
New Update: 4/16/20

Here are reference designs for vehicles.

ROAR Design

BARC Design

Learn more about BARC here.

Courses:

Courses offered at UC Berkeley in Fall 2020 where students can learn more about ROAR.

Intro to Robotics

Fall 2020

Theory and Applications of Virtual Reality and Immersive Computing

Fall 2020

Vehicle Dynamics and Control

Presentations:

ROAR Reference Vehicle Breakdown and Assembly Instructions

Localization Module Presentation

2/7/20 – Control Approaches for Autonomous Racing

For more information, please contact:

Dr. Allen Y. Yang <yang@eecs.berkeley.edu>
Huo Chao Kuan <hc_kuan@berkeley.edu>