发表机构
European Space Agency（欧洲空间局）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对Argonaut月球着陆器，用Julia开发了名为ATLAS的GNC仿真框架，对比MATLAB/Simulink后发现其可支持大规模并行仿真与快速迭代，适用于航天领域的早期设计与研究。
AI 中文摘要
不能，Julia编程语言本身无法实现登月，但它可在登月所需的制导、导航与控制（GNC）算法的设计与分析中发挥关键作用。本文介绍了欧洲空间局（ESA）在Argonaut月球着陆器项目中，使用Julia开发的月球着陆仿真框架。ATLAS（Argonaut Tools for Landing Analysis and Simulation，即Argonaut着陆分析与仿真工具）是一套模块化的分析与仿真工具套件，覆盖Argonaut从下降到着陆的全阶段，在多速率仿真环境中整合了高保真的平动与转动动力学、可变质量特性、推进剂晃动、详细的传感器与执行器模型，以及符合飞行要求的GNC算法。该框架旨在在单一环境中衔接早期原型开发与大规模蒙特卡洛分析。本研究对比了采用Julia与基于MATLAB/Simulink生态系统的成熟GNC开发实践的优势与局限性，结果表明，Julia为机构驱动的研究、早期设计研究及计算密集型闭环仿真提供了强大、灵活且高性能的环境，支持大规模可并行化仿真与快速设计迭代周期。
英文摘要
No, the Julia programming language cannot land on the Moon - but it can play a crucial role in designing and analysing the Guidance, Navigation, and Control (GNC) algorithms required for doing so. This paper presents the development of a lunar landing simulation framework implemented in Julia at the European Space Agency (ESA), within the Argonaut lunar lander programme. ATLAS (Argonaut Tools for Landing Analysis and Simulation) is a modular suite of analysis and simulation tools that cover the complete descent and landing phase of Argonaut, integrating high fidelity translational and rotational dynamics, varying mass properties, propellant sloshing, detailed sensor and actuator models, and flight-representative GNC algorithms within a multi-rate simulation environment. The framework is intended to bridge early-phase prototyping and large-scale Monte Carlo analysis within a single environment. This work evaluates the advantages and limitations of adopting Julia compared to established GNC development practices based on the MATLAB/Simulink ecosystem. The results show that Julia provides a powerful, flexible, and high-performance environment for agency-driven research, early-phase design studies, and computationally intensive closed-loop simulations enabling large-scale, parallelizable simulations and rapid design iteration cycles.
CommentsAuthor draft, presented at the ESA GNC & ICATT Conference 2026
