Publications

The following publications have been produced using BSK-RL and its predecessors. If you have used BSK-RL in your research, please let us know and we will add your publication to the list.

Journal Papers

  1. A. P. Herrmann and H. Schaub, “Monte Carlo Tree Search Methods for the Earth-Observing Satellite Scheduling Problem,” Journal of Aerospace Information Systems, Vol. 19, No. 1, January 2022, pp. 70–82. doi:10.2514/1.I010992

  2. A. Harris, T. Valade, T. Teil and H. Schaub, “Generation of Spacecraft Operations Procedures Using Deep Reinforcement Learning,” Journal of Spacecraft and Rockets, Vol. 59, No. 2, March–April 2022, pp. 611–626. doi:10.2514/1.A35169.

  3. A. P. Herrmann and H. Schaub, “Reinforcement Learning for the Agile Earth-Observing Satellite Scheduling Problem,” IEEE Transactions of Aerospace and Electronic Systems, Vol. 59, No. 5, Oct. 2023, pp. 5235–5247. doi:10.1109/TAES.2023.3251307.

  4. A. Herrmann and H. Schaub, “A Comparative Analysis of Reinforcement Learning Algorithms for Earth-Observing Satellite Scheduling,” Frontiers in Space Technologies, November 29, 2023. doi:10.3389/frspt.2023.1263489.

  5. A. Herrmann, M. Stephenson and H. Schaub, “Single-Agent Reinforcement Learning for Scalable Earth-Observing Satellite Constellation Operations,” Journal of Spacecraft and Rockets. doi:doi.org/10.2514/1.A35736.

  6. A. Herrmann and H. Schaub, “Autonomous Small Body Science Operations Using Reinforcement Learning,” Journal of Aerospace Information Systems.

Conference Papers

  1. A. Harris. T. Teil and H. Schaub, “Spacecraft Decision-Making Autonomy using Deep Reinforcement Learning,” AAS Spaceflight Mechanics Meeting, Maui, Hawaii January 13–17, 2019.

  2. A. Harris and H. Schaub, “Spacecraft Command and Control with Safety Guarantees using Shielded Deep Reinforcement Learning” AIAA SciTech Forum, Orlando, Florida, Jan. 6–10, 2020.

  3. A. Herrmann and H. Schaub, “Monte Carlo Tree Search With Value Networks For Autonomous Spacecraft Operations,” AAS/AIAA Astrodynamics Specialist Conference, Lake Tahoe, CA, Aug. 9–13, 2020.

  4. A. Herrmann and H. Schaub, “Autonomous Spacecraft Tasking using Monte Carlo Tree Search Methods,” AAS/AIAA Space Flight Mechanics Meeting, Charlotte, NC, January 31–February 4, 2021.

  5. A. Herrmann and H. Schaub, “Autonomous On-board Planning for Earth-orbiting Spacecraft,” IEEE Aerospace Conference, Big Sky, MT, March 5–12, 2022.

  6. I. Nazmy, A. Harris, M. Lahijanian and H. Schaub, “Shielded Deep Reinforcement Learning for Multi-Sensor Spacecraft Imaging,” American Control Conference, Atlanta, GA, June 8–10, 2022.

  7. A. Herrmann and H. Schaub, “A Comparison Of Deep Reinforcement Learning Algorithms For Earth-Observing Satellite Scheduling,” AAS/AIAA Spaceflight Mechanics Meeting, Austin, TX, Jan. 15–19, 2023.

  8. V. Bajenaru, A. Herrmann, H. Schaub and S. Philipps, “Command and Control of Satellite Constellations using Explainable Deep Reinforcement Learning,” AAS Rocky Mountain GN&C Conference, Breckenridge, CO, Feb. 2–8, 2023.

  9. A. Herrmann, M. Stephenson and H. Schaub, “Reinforcement Learning for Multi-Satellite Agile Earth Observing Scheduling Under Various Communication Assumptions,” AAS Rocky Mountain GN&C Conference, Breckenridge, CO, Feb. 2–8, 2023.

  10. A. Herrmann and H. Schaub, “Reinforcement Learning For Small Body Science Operations,” AAS Astrodynamics Specialist Conference, Charlotte, North Carolina, August 7–10 2022, Paper No. AAS 22-563.

  11. M. Stephenson and H. Schaub, “Optimal Target Sequencing In The Agile Earth-Observing Satellite Scheduling Problem Using Learned Dynamics,” AAS/AIAA Astrodynamics Specialist Conference, Big Sky, Montana, August 13–17 2023.

  12. M. Stephenson, L. Quevedo Manotovani, S. Phillips and H. Schaub, “Using Enhanced Simulation Environments to Accelerate Reinforcement Learning for Long-Duration Satellite Autonomy,” AIAA Science and Technology Forum and Exposition (SciTech), Orlando, Florida, Jan. 8–12, 2024. doi:10.2514/6.2024-0990.

  13. M. Stephenson and H. Schaub, “Reinforcement Learning for Earth-Observing Satellite Autonomy with Event-Based Task Intervals,” AAS Rocky Mountain GN&C Conference, Breckenridge, CO, Feb. 2–7, 2024.

  14. M. Stephenson, L. Quevedo Mantovani and H. Schaub, Intent Sharing for Emergent Collaboration in Autonomous Earth Observing Constellations,” AAS Rocky Mountain GN&C Conference, Breckenridge, CO, Feb. 2–7, 2024.