Proposal of a Low Cost Navigation System for Starter Teams in Autonomous Racecar Competitions
Keywords: Autonomous Vehicles, State Estimation, Localization, Map-building, Trajectory and Path Planning
AbstractThis article is intended for student teams which aim to enter a autonomous racecar competition. Many starter teams have neither a consolidated knowledge in autonomous system nor a great financial support. Most papers focused on autonomous racecars introduce advanced systems with expensive hardware. Therefore, this work proposes a low-cost and simple navigation system for the autonomous racing problem. This paper focus on a specific event of the Formula Student Driverless competition, but it can serve as basis for other events and competitions. The development of the system is done using the framework ROS and simulated in Gazebo. From this perspective, this work can serve as a guide for starter teams to design their first prototype.