SAGES translates natural-language commands into constraint-respecting spacecraft trajectories, achieving over 90% semantic-behavioral consistency in proximity operations and robotic tests.
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Extends lossless convexification theory for linear time-varying systems with discrete inputs by proving normality preservation under epigraph reformulation and geometric conditions that guarantee the relaxed solution satisfies the original discrete constraints exactly.
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Language-Conditioned Safe Trajectory Generation for Spacecraft Rendezvous
SAGES translates natural-language commands into constraint-respecting spacecraft trajectories, achieving over 90% semantic-behavioral consistency in proximity operations and robotic tests.
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Geometric Conditions for Lossless Convexification in Linear Optimal Control with Discrete-Valued Inputs: Real-Time Implementation for Spacecraft Rendezvous
Extends lossless convexification theory for linear time-varying systems with discrete inputs by proving normality preservation under epigraph reformulation and geometric conditions that guarantee the relaxed solution satisfies the original discrete constraints exactly.