Generative design of periodic orbits in the restricted three-body problem
Gil, Alvaro Francisco and Litteri, Walther and Rodriguez-Fernandez, Victor and Camacho, David and Vasile, Massimiliano (2024) Generative design of periodic orbits in the restricted three-body problem. Other. arXiv, Ithaca, NY. (https://doi.org/10.48550/arXiv.2408.03691)
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Abstract
The Three-Body Problem has fascinated scientists for centuries and it has been crucial in the design of modern space missions. Recent developments in Generative Artificial Intelligence hold transformative promise for addressing this longstanding problem. This work investigates the use of Variational Autoencoder (VAE) and its internal representation to generate periodic orbits. We utilize a comprehensive dataset of periodic orbits in the Circular Restricted Three-Body Problem (CR3BP) to train deep-learning architectures that capture key orbital characteristics, and we set up physical evaluation metrics for the generated trajectories. Through this investigation, we seek to enhance the understanding of how Generative AI can improve space mission planning and astrodynamics research, leading to novel, data-driven approaches in the field.
ORCID iDs
Gil, Alvaro Francisco, Litteri, Walther, Rodriguez-Fernandez, Victor, Camacho, David and Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465;-
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Item type: Monograph(Other) ID code: 90411 Dates: DateEvent7 August 2024PublishedNotes: SPAICE Conference 2024 (7 pages) Subjects: Science > Mathematics > Electronic computers. Computer science
Science > Astronomy
Technology > Motor vehicles. Aeronautics. Astronautics > Astronautics. Space travelDepartment: Faculty of Engineering > Mechanical and Aerospace Engineering
Technology and Innovation Centre > Advanced Engineering and Manufacturing
Strategic Research Themes > Ocean, Air and SpaceDepositing user: Pure Administrator Date deposited: 29 Aug 2024 13:44 Last modified: 08 Oct 2024 00:06 URI: https://strathprints.strath.ac.uk/id/eprint/90411