Open Source Software

At the Institute of Automotive Technology we are developing software and algorithms in various areas, which we are making available to the public.

For this purpose we have created our own Github account, where all projects, software and algorithms of the FTM research are stored: TUM FTM Github

We look forward to your feedback on our open source software. We would be pleased if you use the GitHub Issue Tracker to share your ideas for improving the code.

Open Source Software for Autonomous Racing

The following table shows our open source contributions in the various areas of autonomous motorsport. Our current software stack will be available soon.

Module	Link	Responsible
Perception	https://github.com/TUMFTM/CameraRadarFusionNet (2019)	TUM FTM
Tracking	https://github.com/TUMFTM/FusionTracking (2022)	TUM FTM
Prediction	https://github.com/TUMFTM/MixNet (2022)	TUM FTM
Local Planning	https://github.com/TUMFTM/GraphBasedLocalTrajectoryPlanner (2019) https://github.com/TUMFTM/TrajectorySupervisor (2021) https://github.com/TUMRT/sampling_based_3D_local_planning (2024)	TUM AVS TUM Lehrstuhl für Regelungstechnik
Raceline Planning	https://github.com/TUMFTM/global_racetrajectory_optimization (2021) https://github.com/TUMRT/online_3D_racing_line_planning (2023)	TUM AVS TUM Lehrstuhl für Regelungstechnik
Control	https://github.com/TUMFTM/mod_vehicle_dynamics_control (2022)	TUM Lehrstuhl für Regelungstechnik TUM FTM
Localization	https://github.com/TUMFTM/ORB_SLAM3_RGBL (2023) https://github.com/TUMFTM/orbslam-map-saving-extension (2020)	TUM FTM
Simulation	https://github.com/TUMFTM/race-simulation (2021) https://github.com/TUMFTM/laptime-simulation (2021) https://github.com/TUMFTM/Sim2RealDistributionAlignedDataset (2023) https://github.com/TUMFTM/sim_vehicle_dynamics (2022)	TUM FTM