Digital and Robotic Twinning for Validation of Proximity Operations and Formation Flying

TL;DR

This paper presents a comprehensive digital and robotic twinning framework for validating spacecraft guidance, navigation, and control systems in proximity operations and formation flying, bridging simulation and real-world testing.

Contribution

It introduces a modular, end-to-end hybrid twinning framework combining software and hardware-in-the-loop testing for spacecraft GNC validation.

Findings

Demonstrated consistency between simulation and hardware tests.

Validated GNC performance across multiple operational modes.

Established a reliable pipeline for GNC system verification.

Abstract

Spacecraft Rendezvous, Proximity Operations (RPO), and Formation Flying (FF) rely on safety-critical guidance, navigation and control (GNC) that must satisfy stringent performance and robustness requirements. However, verifying GNC performance is challenging due to the complexity and inaccessibility of the space environment, necessitating a verification and validation (V\&V) process that bridges simulation and real-world behavior. This paper contributes a unified, closed-loop, end-to-end digital and robotic twinning framework that enables software- and hardware-in-the-loop testing of spacecraft GNC systems. The framework is designed for modularity and flexibility, supporting interchangeable sensing modalities, control algorithms, and operational regimes. The digital twin includes an event-driven faster-than-real-time simulation environment to support rapid prototyping. The architecture is augmented with hardware-based robotic testbeds from 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 developed at SLAB. This paper introduces the hybrid twinning framework, summarizes calibration and error characterization of the robotic testbeds, and evaluates GNC performance across multiple operational modes in a full-range RPO scenario in LEO. The results demonstrate consistency between software- and hardware-in-the-loop tests with clear explainability for deviations in performance, thus validating the hybrid twinning pipeline as a reliable framework for realistic assessment and verification of GNC systems.