Autonomous Multi-Agent AI Systems for Satellite Mission Design.
| dc.centro | E.T.S.I. Informática | es_ES |
| dc.contributor.author | Navarro, Tomás | |
| dc.contributor.author | Stroescu, Ana | |
| dc.contributor.author | Izzo, Dario | |
| dc.contributor.author | Gálvez-Rojas, Sergio | |
| dc.contributor.author | López-Valverde, Francisco | |
| dc.date.accessioned | 2025-10-21T07:16:00Z | |
| dc.date.available | 2025-10-21T07:16:00Z | |
| dc.date.created | 2025 | |
| dc.date.issued | 2025-10 | |
| dc.departamento | Lenguajes y Ciencias de la Computación | es_ES |
| dc.description | https://conferences.ieeeauthorcenter.ieee.org/author-ethics/guidelines-and-policies/post-publication-policies/ | es_ES |
| dc.description.abstract | The integration of Artificial Intelligence (AI) agents in supporting engineering design is rapidly gaining attention due to their potential to accelerate decision-making, optimise designs, and reduce costs. This paper presents a comprehensive evaluation of two different AI agentic systems, each system run by a different LLM (Large Language Model): DeepSeek-R1-70B and GPT-4o. The agents are evaluated in supporting satellite constellation design across key domains: market analysis, frequency filing, mission planning, payload feasibility, and cost analysis. Four distinct satellite designs were analysed per model, and expert evaluations were conducted to assess their effectiveness. This study highlights both the benefits and shortcomings of AI agents in satellite design, providing a comparative assessment and discussing implications for future AI-driven space mission planning. | es_ES |
| dc.identifier.doi | 10.1109/ICMLT65785.2025.11192855 | |
| dc.identifier.uri | https://hdl.handle.net/10630/40345 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | IEEE | es_ES |
| dc.relation.eventdate | 23-25 de mayo de 2025 | es_ES |
| dc.relation.eventplace | Helsinki, Finlandia | es_ES |
| dc.relation.eventtitle | 10th International Conference on Machine Learning Technologies (ICMLT) | es_ES |
| dc.rights.accessRights | open access | es_ES |
| dc.subject | Inteligencia artificial | es_ES |
| dc.subject | Sistemas de comunicaciones inalámbricos | es_ES |
| dc.subject | Aprendizaje automático (Inteligencia artificial) | es_ES |
| dc.subject | Proceso en lenguaje natural (Informática) | es_ES |
| dc.subject | Procesado de señales | es_ES |
| dc.subject | Satélites artificiales | es_ES |
| dc.subject | Exploración espacial | es_ES |
| dc.subject.other | Satellite constellations | es_ES |
| dc.subject.other | Satellites | es_ES |
| dc.subject.other | Space missions | es_ES |
| dc.subject.other | Large language models | es_ES |
| dc.subject.other | Frequency-domain analysis | es_ES |
| dc.subject.other | Machine learning | es_ES |
| dc.subject.other | Planning | es_ES |
| dc.subject.other | Device-to-device communication | es_ES |
| dc.subject.other | Artificial intelligence | es_ES |
| dc.subject.other | Payloads | es_ES |
| dc.title | Autonomous Multi-Agent AI Systems for Satellite Mission Design. | es_ES |
| dc.type | conference output | es_ES |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | d978d7e6-74cb-4240-bb3a-5693f84d80ca | |
| relation.isAuthorOfPublication | 02fc094f-5f93-4ee1-9f93-c717c528c11b | |
| relation.isAuthorOfPublication.latestForDiscovery | d978d7e6-74cb-4240-bb3a-5693f84d80ca |
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