Future Aircraft Sizing Tool - Unmanned Aerial Vehicles

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.

🚀 Quick start

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.

📚 Citation

If you use FAST-UAV as part of your work in a scientific publication, please consider citing the following papers:

@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},
}

🔥 Related publications

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

📝 License

The software is released under The GNU General Public License v3.0.

🤝 Questions and contributions

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 scott.delbecq@isae-supaero.fr
• Félix POLLET felix.pollet@isae-supaero.fr
• Marc BUDINGER mbudinge@insa-toulouse.fr

For developers, please follow the following procedure:

1. Fork the GitHub repository of FAST-UAV
2. Clone your forked repository onto your local machine with git clone
3. cd into your FAST-UAV project and install the required dependencies with Poetry using the poetry install command.
4. Start making changes to the forked repository
5. Open a pull request to merge those changes back into the original repository of FAST-UAV.