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.

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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
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Autonomous Multi-Agent AI Systems for Satellite Mission Design

Sergio Gálvez, Dario Izzo, Tomás Navarro, Francisco L. Valverde et al.
Scheduling and Optimization Algorithms
article

Autonomous Multi-Agent AI Systems for Satellite Mission Design

Sergio Gálvez, Dario Izzo, Tomás Navarro, Francisco L. Valverde, Ana Stroescu
article en

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.

University of Lagos (NG), European Space Agency (FR), European Centre for Space Applications and Telecommunications (GB), European Space Research and Technology Centre (NL)
Openalex Percentile: Top 59%
Scheduling and Optimization Algorithms
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