Racing With ROS 2 A Navigation System for an Autonomous Formula Student Race Car
This work addresses the complexity of autonomous racing for Formula Student teams, though it is incremental as it applies existing ROS 2 tools to a specific domain.
The paper tackles the challenge of high-speed navigation for autonomous Formula Student race cars by presenting an open-source solution using ROS 2's navigation stack, comparing it against traditional custom programs to lower the entry barrier for teams.
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.