Autonomous Multi-Agent AI Systems for Satellite Mission Design
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.
Authors
- Sergio Gálvez (ORCID: https://orcid.org/0000-0003-4743-2807)
- Dario Izzo (ORCID: https://orcid.org/0000-0002-9846-8423)
- Tomás Navarro
- Francisco L. Valverde
- Ana Stroescu
Institutions
- University of Lagos (NG)
- European Space Agency (FR)
- European Centre for Space Applications and Telecommunications (GB)
- European Space Research and Technology Centre (NL)
Publication Details
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1109/icmlt65785.2025.11192855
- Primary Topic
- Scheduling and Optimization Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00