In the last three years, numerous algorithms and tools for autonomous driving have been developed in various research projects here at the FTM Institute. This software is then extended by special data sets. All this knowledge has been made available on Github Open Source and offers other scientists and developers the possibility to use our software as a benchmark or starting point for their own development. We are looking forward to feedback from the community and will continue to provide more algorithms, tools and data in 2020. An overview of the most important Github repositories for autonomous driving can be found here:
- Graph-based local trajectory planner for a race vehicle in a dynamic environment
- Scenario Architect for the creation of short scene snapshots for autonomous driving benchmarks
- Optimization algorithm for the creation of global, optimal raceline
- Path and velocity controller for an autonomous racecar
- Neural Network for Object Detection with Camera and Radar Data
- Vehicle dynamics simulation for autonomous vehicles
- Library with functions for trajectory planning
- Database with maps of international racetracks
- Quasi-static laptime simulation
- Recursive Uncertainty Model Identification
- ORB-SLAM2 Map Saving Extension