AI-Powered Augmented Reality for Satellite Assembly, Integration and Test

TL;DR

This paper demonstrates how AI-powered augmented reality systems, using real-time computer vision and synthetic data, can significantly improve satellite assembly and testing processes by enhancing accuracy and efficiency.

Contribution

It introduces a novel AR system integrated with AI models trained on synthetic data, including the SAMAL tool for rapid automatic data annotation, tailored for satellite AIT workflows.

Findings

AI models achieved over 70% accuracy in object recognition.

Detection model exceeded 95% accuracy, ensuring high reliability.

Synthetic data and SAMAL significantly sped up data annotation processes.

Abstract

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.