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Found 2 papers, 1 papers with code
Improving Computational Efficiency for Powered Descent Guidance via Transformer-based Tight Constraint Prediction
T-PDG uses data from prior runs of trajectory optimization algorithms to train a transformer neural network, which accurately predicts the relationship between problem parameters and the globally optimal solution for the powered descent guidance problem.
Transformer-based Atmospheric Density Forecasting
As the peak of the solar cycle approaches in 2025 and the ability of a single geomagnetic storm to significantly alter the orbit of Resident Space Objects (RSOs), techniques for atmospheric density forecasting are vital for space situational awareness.
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