Borrick, Daniel (2024) FSAE Autonomous Racing Development. [USQ Project]
Abstract
This thesis focuses on the development and testing of an autonomous racing system designed for a scale-model vehicle, inspired by FSAE racing requirements. The system integrates
advanced perception techniques using vision-based object detection and LiDAR for obstacle tracking, with the goal of creating an efficient control loop for vehicle navigation. Various localisation algorithms including EKF and FastSLAM 2.0 are implemented for real-time mapping and state estimation. Additional scale-model hardware was also developed and tested for the purposes of future development. This work leverages both simulation tools and real-world testing platforms, making use of a ROS2-based architecture for modular development.
The research aims to provide a foundation for further development in autonomous racing for FSAE at USQ, using a custom-built vehicle and sensor setup. Simulation and real-world results, including visualisation tools developed in RViz, will highlight system performance.
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Statistics for this ePrint Item |
| Item Type: | USQ Project |
|---|---|
| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Current – Faculty of Health, Engineering and Sciences - School of Engineering (1 Jan 2022 -) |
| Supervisors: | Lowe, Tobias |
| Qualification: | Bachelor of Engineering (Honours) |
| Date Deposited: | 09 Mar 2026 03:56 |
| Last Modified: | 09 Mar 2026 03:56 |
| Uncontrolled Keywords: | autonomous racing system; FSAE |
| URI: | https://sear.unisq.edu.au/id/eprint/53020 |
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