Autonomous spacecraft inspection and docking missions require controllers that can guarantee safety under thrust constraints and uncertainty. Input-constrained control barrier functions (ICCBFs) provide a framework for safety certification under bounded actuation; however, conventional ICCBF formulations can be overly conservative and exhibit limited robustness to uncertainty, leading to high fuel consumption and reduced mission feasibility. This paper proposes a framework in which the full hierarchy of class-$\mathcal{K}$ functions defining the ICCBF recursion is parameterized and learned, enabling localized shaping of the safe set and reduced conservatism. A control margin is computed efficiently using differential algebra to enable the learned continuous-time ICCBFs to be implemented on time-sampled dynamical systems typical of spacecraft proximity operations. A meta-reinforcement learning scheme is developed to train a policy that generates ICCBF parameters over a distribution of hidden physical parameters and uncertainties, using both multilayer perceptron (MLP) and recurrent neural network (RNN) architectures. Simulation results on cruise control, spacecraft inspection, and docking scenarios demonstrate that the proposed approach maintains safety while reducing fuel consumption and improving feasibility relative to fixed class-$\mathcal{K}$ ICCBFs, with the RNN showing a particularly strong advantage in the more complex inspection case.
Safety-Guaranteed Imitation Learning from Nonlinear Model Predictive Control for Spacecraft Close Proximity Operations
Space Applications Group, e:fs TechHub GmbH（空间应用组，e:fs科技枢纽 GmbH）；Faculty of Electrical Engineering and Information Technology, Ingolstadt University of Applied Sciences（电气工程与信息科技学院，因戈尔施塔特应用技术大学）
TempoNet: Slack-Quantized Transformer-Guided Reinforcement Scheduler for Adaptive Deadline-Centric Real-Time Dispatchs
University of Macau（澳门大学）；Tsinghua University（清华大学）；Northeast Normal University（东北师范大学）；Shanghai AI Laboratory（上海人工智能实验室）；The Australian National University（澳大利亚国立大学）；Peking University（北京大学）；Harbin University of Science and Technology（哈尔滨理工大学）；Renmin University of China（中国人民大学）；Adelaide University（阿德莱德大学）
