A neural BRAT framework trained with curriculum-driven MPC supervision approximates HJ reach-avoid value functions and deploys them via gradient and augmented-MPC controllers, outperforming baselines on 6D and 13D docking tasks.
Model predictive control in aerospace systems: Current state and opportunities
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Neural Backward Reach-Avoid Tubes with MPC Supervision for High-Dimensional Systems: An Application to Safe Spacecraft Docking
A neural BRAT framework trained with curriculum-driven MPC supervision approximates HJ reach-avoid value functions and deploys them via gradient and augmented-MPC controllers, outperforming baselines on 6D and 13D docking tasks.