QUT-Motorsport/QUTMS_Driverless
Welcome to the QUTMS Driverless team repository, used to develop perception, planning and control pipelines in ROS2 for a driverless FSAE racecar
This project provides the complete software system for an autonomous Formula SAE (FSAE) racecar, handling everything from perceiving the track to planning and executing the drive. It takes sensor data from cameras and LiDAR as input and produces commands for steering, throttle, and braking. The primary users are student motorsport teams and researchers building or experimenting with self-driving racecars.
Use this if you are a student or researcher developing an autonomous racing vehicle and need a robust, competition-tested software stack for perception, planning, and control.
Not ideal if you are looking for a general-purpose autonomous driving system for passenger vehicles or commercial applications, as it's specifically tailored for the FSAE racing environment.
Stars
66
Forks
6
Language
Python
License
MIT
Category
Last pushed
Jan 29, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/QUT-Motorsport/QUTMS_Driverless"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
carla-simulator/carla
Open-source simulator for autonomous driving research.
OpenHUTB/hutb
人车模拟器
thomasfermi/Algorithms-for-Automated-Driving
Each chapter of this (mini-)book guides you in programming one important software component for...
ProjectNeura/LEADS
Enable your racing car with powerful, data-driven instrumentation, control, and analysis...
deepdrive/deepdrive
Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving