The integration of Artificial Intelligence (AI) and Augmented Reality (AR) is set to transform satellite Assembly, Integration, and Testing (AIT) processes by enhancing precision, minimizing human error, and improving operational efficiency in cleanroom environments. This paper presents a technical description of the European Space Agency's (ESA) project "AI for AR in Satellite AIT," which combines real-time computer vision and AR systems to assist technicians during satellite assembly. Leveraging Microsoft HoloLens 2 as the AR interface, the system delivers context-aware instructions and real-time feedback, tackling the complexities of object recognition and 6D pose estimation in AIT workflows. All AI models demonstrated over 70% accuracy, with the detection model exceeding 95% accuracy, indicating a high level of performance and reliability. A key contribution of this work lies in the effective use of synthetic data for training AI models in AR applications, addressing the significant challenges of obtaining real-world datasets in highly dynamic satellite environments, as well as the creation of the Segmented Anything Model for Automatic Labelling (SAMAL), which facilitates the automatic annotation of real data, achieving speeds up to 20 times faster than manual human annotation. The findings demonstrate the efficacy of AI-driven AR systems in automating critical satellite assembly tasks, setting a foundation for future innovations in the space industry.

翻译：人工智能（AI）与增强现实（AR）的融合，旨在通过提升洁净室环境中的操作精度、减少人为错误并提高作业效率，从而变革卫星的装配、集成与测试流程。本文对欧洲空间局的“卫星AIT中用于AR的AI”项目进行了技术描述，该项目结合实时计算机视觉与AR系统，为技术人员在卫星装配过程中提供协助。该系统以Microsoft HoloLens 2作为AR交互界面，提供情境感知的指令与实时反馈，以应对AIT工作流程中物体识别与六维位姿估计的复杂性。所有AI模型均展现出超过70%的准确率，其中检测模型的准确率超过95%，表明其具备高水平的性能与可靠性。本工作的一个关键贡献在于，有效利用合成数据训练AR应用中的AI模型，解决了在高度动态的卫星环境中获取真实世界数据集的重大挑战；同时，创建了用于自动标注的分割一切模型，该模型促进了真实数据的自动标注，其速度比人工标注快达20倍。研究结果证明了AI驱动的AR系统在自动化关键卫星装配任务中的有效性，为未来航天工业的创新奠定了基础。