Digital Twins and Modelling for Spacecraft Science Operations: Application to Surface Interaction and Sampling on Small Solar-System Bodies
Abstract. The increasing number of space exploration missions presents a novel challenge with regards to planning and operations. Current architectures are composed of distinct teams and models performing separate tasks like navigation, planning, and science, which can lead to inefficiencies and delays. This work proposes a Digital Twin (DT) architecture which supports end-to-end mission design, operations, and scientific analysis. The proposed DT combines models of the spacecraft, its scientific payloads, and the target body, linked through a data processing layer that enables continuous monitoring, simulation, and decision support. A case study of a spacecraft exploring an asteroid and interacting with its surface through a lander and sampling arm is presented. This example specifically shows the importance of reduced order models (ROMs) to efficiently predict and interpret surface interactions. This approach highlights the potential of integrated DT architectures to enhance coordination, adaptability, and scientific return in future deep space missions.