Digital and Robotic Twinning for Validation of Proximity Operations and Formation Flying
This provides a reliable verification framework for spacecraft rendezvous and formation flying systems, though it is incremental as it builds on existing twinning concepts.
The paper tackles the challenge of validating safety-critical Guidance Navigation and Control (GNC) systems for spacecraft operations by developing a unified digital and robotic twinning framework, which demonstrates consistency between digital and robotic twins in a full-range Low-Earth Orbit mission scenario.
In spacecraft Rendezvous, Proximity Operations (RPO), and Formation Flying (FF), the Guidance Navigation and Control (GNC) system is safety-critical and must meet strict performance requirements. However, validating such systems is challenging due to the complexity of the space environment, necessitating a verification and validation (V&V) process that bridges simulation and real-world behavior. The key contribution of this paper is a unified, end-to-end digital and robotic twinning framework that enables software- and hardware-in-the-loop testing for multi-modal GNC systems. The robotic twin includes three testbeds at Stanford's Space Rendezvous Laboratory (SLAB): the GNSS and Radiofrequency Autonomous Navigation Testbed for Distributed Space Systems (GRAND) to validate RF-based navigation techniques, and the Testbed for Rendezvous and Optical Navigation (TRON) and Optical Stimulator (OS) to validate vision-based methods. The test article for this work is an integrated multi-modal GNC software stack for RPO and FF developed at SLAB. This paper introduces the hybrid framework and summarizes calibration and error characterization for the robotic twin. Then, the GNC stack's performance and robustness is characterized using the integrated digital and robotic twinning pipeline for a full-range RPO mission scenario in Low-Earth Orbit (LEO). The results shown in the paper demonstrate consistency between digital and robotic twins, validating the hybrid twinning pipeline as a reliable framework for realistic assessment and verification of GNC systems.