arXiv:2507.20034cs.ROcs.CV2025-07

构建软硬件协同的太空飞行验证框架,提升导航控制系统的可靠性。

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

  • 用数字孪生+机器人实验床实现软硬件闭环测试
  • 在低轨场景下多模式验证导航控制性能一致
  • 适合航天器控制系统研发与测试团队参考

航天器交会、近距离操作(RPO)和编队飞行(FF)依赖于高安全性的制导、导航与控制(GNC)系统,其性能必须满足严格要求。然而,由于空间环境复杂且难以接近,GNC性能验证面临挑战,需通过仿真与实测之间的验证与确认(V&V)流程来衔接。本文提出一个统一的闭环端到端数字与机器人孪生框架,支持软件及硬件在环的GNC系统测试。该框架具备模块化与灵活性,可替换传感方式、控制算法与运行模式。数字孪生部分包含事件驱动的超实时仿真环境,用于快速原型开发。系统集成斯坦福大学空间交会实验室(SLAB)的两个机器人测试平台:基于GNSS与射频的分布式系统导航测试台(GRAND),用于验证射频导航技术;以及交会与光学导航测试台(TRON)与光学模拟器(OS),用于验证视觉导航方法。本研究采用SLAB开发的多模态集成式GNC软件栈作为测试对象。论文介绍该混合孪生框架,总结测试平台的标定与误差特性,并在近地轨道(LEO)全范围RPO场景中评估多种运行模式下的GNC性能。结果表明,软硬件在环测试表现一致,偏差具有可解释性,验证了该混合孪生流程作为真实系统评估与验证的可靠框架。

原文摘要 · Abstract (English)

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.

航天控制数字孪生机器人测试GNC系统

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