FW-JSBGym

RL compatible framework of the JSBSim simulator. All control algorithms, training and testing scripts are on the FWFlightControl repository.

Installation

Requires python 3.10

If you wish to use the FlightGear visualization:

• Install the AppImage from here and place the file into your $HOME/Apps/ directory (create it if it does not exist).
• Launch the AppImage for it to create all the config and data folders.
• Copy the contents of fgdata/Aircraft/ of the repository in the $HOME/Apps/fgdata/Aircraft/.

pip install -r pip_requirements.txt
pip install -e .

or

conda env create --file environment.yml
pip install -e .

Directory organization

• envs/ contains the JSBSimEnv abstract class, describing the basis of a JSBSim env.
  • tasks/attitude_control contains the child classes of JSBSimEnv for the attitude control tasks.
• fdm_descriptions/ JSBSim description of the c172p and x8 aircrafts.
• fgdata/ FlightGear visualization files.
• models/ Saves of NN models.
• simulation/jsb_simulation.py contains core functions of JSBSim for setting up, stepping the simulation, accessing properties and converting units.
• utils/jsbsim_properties.py references properties to be accessed, inspired from existing work: https://github.com/Gor-Ren/gym-jsbsim/blob/master/gym_jsbsim/properties.py
• visualizers/
  • attitude_control_telemetry.py handles the 'live' plot visualization of a flight.
  • visualizer.py handles FlightGear viz or calls the live plot visualizer.

Citation

@inproceedings{olivares2024mfvsmb,
  title={Model-Free versus Model-Based Reinforcement Learning for Fixed-Wing UAV Attitude Control Under Varying Wind Conditions}, 
  author={David Olivares and Pierre Fournier and Pavan Vasishta and Julien Marzat},
  booktitle={International Conference on Informatics in Control, Automation and Robotics (ICINCO)},
  year={2024}
}