basilisk-docker

Docker-based containerization workflow for the Basilisk astrodynamics simulation framework, encapsulating the complete build environment within a portable Docker container to enable reproducible GN&C simulations across heterogeneous development systems.

Requirements

• Docker Desktop
• VS Code (recommended)

Quick Start

git clone https://github.com/theinfinitelabs/basilisk-docker.git
cd basilisk-docker
./build-basilisk.sh

Or manually:

docker compose up -d --build

To open a terminal inside the running container:

docker exec -it basilisk_gnc bash

Notes

• The Dockerfile is located at docker/Dockerfile
• Compatible with Ubuntu 22.04 and Python 3.10
• First-time build takes approximately 15-20 minutes
• Subsequent rebuilds use Docker layer caching and are significantly faster
• The de430.bsp SPICE ephemeris file is not included due to size; see Section 3 of the companion paper for retrieval instructions
• Running each scenario generates a .bin file in the same directory, which can be opened in Vizard for 3D visualization.

Development History

The Docker configuration in this repository originated from simulation environment work begun in 2021. The workflow was formalized and presented as a workshop at the 46th Rocky Mountain AAS GN&C Conference in February 2024 (Zenodo: 10.5281/zenodo.15008785), and is documented in the companion paper listed above.

Citation

If you use this software infrastucture or workflow in your research, please cite the appropriate reference:

Software:

@software{gupta2026basilisk,
  author       = {Gupta, Anubhav},
  title        = {Basilisk and Docker for Reproducible GN\&C Simulation},
  year         = {2026},
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.20132421},
  url          = {https://github.com/theinfinitelabs/basilisk-docker}
}

Paper:

@article{gupta2026basiliskpaper,
  author       = {Gupta, Anubhav},
  title        = {Basilisk and Docker for Reproducible {GN\&C} Simulation: A Workflow Reference},
  journal      = {arXiv preprint},
  year         = {2026},
  eprint       = {2605.12443},
  archivePrefix = {arXiv},
  primaryClass = {eess.SY},
  doi          = {10.48550/arXiv.2605.12443}
}

Acknowledgments

The author thanks Dr. Hanspeter Schaub and the AVS Laboratory at the University of Colorado Boulder for developing Basilisk.