Racing With ROS 2 A Navigation System for an Autonomous Formula Student Race Car

TL;DR

This paper introduces an open-source ROS 2-based navigation system for autonomous Formula Student race cars, comparing it with traditional solutions to lower entry barriers and serve as a tutorial for similar applications.

Contribution

It provides a comparative analysis of ROS 2 navigation libraries versus traditional methods and offers a comprehensive tutorial for autonomous racing applications.

Findings

ROS 2 navigation stack performs comparably to custom solutions

Open-source tools reduce development complexity

The approach facilitates entry into autonomous racing

Abstract

The advent of autonomous vehicle technologies has significantly impacted various sectors, including motorsport, where Formula Student and Formula: Society of Automotive Engineers introduced autonomous racing classes. These offer new challenges to aspiring engineers, including the team at QUT Motorsport, but also raise the entry barrier due to the complexity of high-speed navigation and control. This paper presents an open-source solution using the Robot Operating System 2, specifically its open-source navigation stack, to address these challenges in autonomous Formula Student race cars. We compare off-the-shelf navigation libraries that this stack comprises of against traditional custom-made programs developed by QUT Motorsport to evaluate their applicability in autonomous racing scenarios and integrate them onto an autonomous race car. Our contributions include quantitative and qualitative comparisons of these packages against traditional navigation solutions, aiming to lower the entry barrier for autonomous racing. This paper also serves as a comprehensive tutorial for teams participating in similar racing disciplines and other autonomous mobile robot applications.