Safety-Aware Residual Reinforcement Learning for Spacecraft Formation with Coupled Relative Translation and Attitude Dynamics

This paper studies leader–follower spacecraft formation control with coupled relative translation and attitude dynamics under actuator-effectiveness uncertainty, bounded disturbances, and safety constraints. A safety-aware residual reinforcement learning framework is developed by combining a nominal controller, a structured policy, and an online safety filter. Relative-degree decoupling is used to construct affine safe command inequalities, and a recursive safety filter maintains feasibility through backup-sequence update. Simulation results show improved tracking and training convergence over pure policy learning and single-step shielding, while maintaining near-zero safety violation and moderate online computation cost.

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Publication Details

Journal
Guidance Navigation and Control
Published
2026-07-28
DOI
https://doi.org/10.1142/s2737480726400108
Primary Topic
Spacecraft Dynamics and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Safety-Aware Residual Reinforcement Learning for Spacecraft Formation with Coupled Relative Translation and Attitude Dynamics

Di Huang, Yuhan Sun, Zhijun Li
Guidance Navigation and Control
Spacecraft Dynamics and Control
article

Safety-Aware Residual Reinforcement Learning for Spacecraft Formation with Coupled Relative Translation and Attitude Dynamics

Di Huang, Yuhan Sun, Zhijun Li
article en

Abstract

This paper studies leader–follower spacecraft formation control with coupled relative translation and attitude dynamics under actuator-effectiveness uncertainty, bounded disturbances, and safety constraints. A safety-aware residual reinforcement learning framework is developed by combining a nominal controller, a structured policy, and an online safety filter. Relative-degree decoupling is used to construct affine safe command inequalities, and a recursive safety filter maintains feasibility through backup-sequence update. Simulation results show improved tracking and training convergence over pure policy learning and single-step shielding, while maintaining near-zero safety violation and moderate online computation cost.

Guidance Navigation and Control
Wuhan University (CN), Institute of Geodesy and Geophysics (CN), Wuchang University of Technology (CN), Wuhan University of Science and Technology (CN), Hubei University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 5%
Spacecraft Dynamics and Control
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Safety-Aware Residual Reinforcement Learning for Spacecraft Formation with Coupled Relative Translation and Attitude Dynamics — Di Huang, Yuhan Sun, et al. · Guidance Navigation and Control (2026) | TGRS Research Map | TGRS