FAST-UAV is a Python tool dedicated to optimal drone design with a multi-disciplinary approach.
Based on the FAST-OAD and OpenMDAO frameworks, it allows to easily switch between models to address different types of configurations.
Currently, FAST-UAV is bundled with analytical models for multi-rotor, fixed-wing and quad-plane (hybrid VTOL) UAVs.
FAST-UAV requires Python 3.8 or 3.9. It is recommended to install FAST-UAV in a virtual environment (conda, venv...):
conda create --name <env_name> python=3.9
conda activate <env_name>
To install FAST-UAV, run the following commands in a terminal:
pip install fastuav
Now that FAST-UAV is installed, you can start using it through Jupyter notebooks.
To do so, create a new folder for FAST-UAV, cd into this folder, and type this command in your terminal:
fastoad notebooks -p fastuav
Then run the Jupyter server as indicated in the obtained message.
This project is part of Félix Pollet's PhD thesis, which is available here. If you use FAST-UAV as part of your work in a scientific publication, please consider citing the following papers:
@phdthesis{pollet_design_2024,
type = {{PhD} {Thesis}},
title = {Design optimization of unmanned aerial vehicles : a multidisciplinary approach with uncertainty, fault-tolerance, and environmental impact assessments},
url = {http://www.theses.fr/2024ESAE0013/document},
school = {Institut Supérieur de l'Aéronautique et de l'Espace},
author = {Pollet, F{\'e}lix},
collaborator = {Moschetta, Jean-Marc and Budinger, Marc and Delbecq, Scott},
month = mar,
year = {2024},
}
@inproceedings{pollet2022common,
title = {A common framework for the design optimization of fixed-wing, multicopter and {VTOL} {UAV} configurations},
author = {Pollet, F{\'e}lix and Delbecq, Scott and Budinger, Marc and Moschetta, Jean-Marc and Liscou{\"e}t, Jonathan},
booktitle = {33rd {Congress} of the {International} {Council} of the {Aeronautical} {Sciences}},
address = {Stockholm, Sweden},
month = sep,
year = {2022},
}
@inproceedings{pollet2021design,
title = {Design optimization of multirotor drones in forward flight},
author = {Pollet, F{\'e}lix and Delbecq, Scott and Budinger, Marc and Moschetta, Jean-Marc},
booktitle = {32nd {Congress} of the {International} {Council} of the {Aeronautical} {Sciences}},
address = {Shanghai, China},
month = sep,
year = {2021},
}
@article{delbecq2020efficient,
title = {Efficient sizing and optimization of multirotor drones based on scaling laws and similarity models},
author = {Delbecq, Scott and Budinger, Marc and Ochotorena, Aithor and Reysset, Aur{\'e}lien and Defay, Francois},
journal = {Aerospace Science and Technology},
volume = {102},
doi = {10.1016/j.ast.2020.105873},
month = jul,
year = {2020},
pages = {105873},
}
M. Budinger, A. Reysset, A. Ochotorena, and S. Delbecq. Scaling laws and similarity models for the preliminary design of multirotor drones. Aerospace Science and Technology, 2020, 98, pp.1-15. https://doi.org/10.1016/j.ast.2019.105658. https://hal.science/hal-02997598.
S. Delbecq, M. Budinger, A. Ochotorena, A. Reysset, and F. Defay. Efficient sizing and optimization of multirotor drones based on scaling laws and similarity models. Aerospace Science and Technology, 2020, 102, pp.1-23. https://doi.org/10.1016/j.ast.2020.105873. https://hal.science/hal-02997596.
F. Pollet, S. Delbecq, M. Budinger, and J.-M. Moschetta. Design optimization of multirotor drones in cruise. 32nd Congress of the International Council of the Aeronautical Sciences, Sep 2021, Shanghai, China. https://hal.science/hal-03832135/.
S. Delbecq, M. Budinger, C. Coic, and N. Bartoli. Trajectory and design optimization of multirotor drones with system simulation. AIAA Scitech 2021 Forum, Jan. 2021, VIRTUAL EVENT, United States. https://doi.org/10.2514/6.2021-0211. https://hal.science/hal-03121520.
J. Liscouet, F. Pollet, J. Jézégou, M. Budinger, S. Delbecq, and J.-M. Moschetta. A Methodology to Integrate Reliability into the Conceptual Design of Safety-Critical Multirotor Unmanned Aerial Vehicles. Aerospace Science and Technology, 2022, 127, pp.107681. https://doi.org/10.1016/j.ast.2022.107681. https://hal.science/hal-03956142.
F. Pollet, S. Delbecq, M. Budinger, J.-M. Moschetta, and J. Liscouët. A Common Framework for the Design Optimization of Fixed-Wing, Multicopter and VTOL UAV Configurations. 33rd Congress of the International Council of the Aeronautical Sciences, Sep. 2022, Stockholm, Sweden. https://hal.science/hal-03832115/
F. Pollet, M. Budinger, S. Delbecq, J. -M. Moschetta, and J. Liscouët. Quantifying and Mitigating Uncertainties in Design Optimization Including Off-the-Shelf Components: Application to an Electric Multirotor UAV. Aerospace Science and Technology, 2023, pp.108179. https://doi.org/10.1016/j.ast.2023.108179.
F. Pollet, M. Budinger, S. Delbecq, J. -M. Moschetta, and T. Planès. Environmental Life Cycle Assessments for the Design Exploration of Electric UAVs. Aerospace Europe Conference 2023 – 10th EUCASS – 9th CEAS, Jul. 2023, Lausanne, Switzerland. https://doi.org/10.13009/EUCASS2023-548. https://hal.science/hal-04229799.
DroneApp sizing tool
The software is released under The GNU General Public License v3.0.
Feel free to contact us if you have any question or suggestion, or if you wish to contribute with us on FAST-UAV!
- Scott DELBECQ [email protected]
- Félix POLLET [email protected]
- Marc BUDINGER [email protected]
For developers, please follow the following procedure:
- Fork the GitHub repository of FAST-UAV
- Clone your forked repository onto your local machine with
git clone cdinto your FAST-UAV project and install the required dependencies with Poetry using thepoetry installcommand.- Start making changes to the forked repository
- Open a pull request to merge those changes back into the original repository of FAST-UAV.