Improving Computational Efficiency for Powered Descent Guidance via Transformer-based Tight Constraint Prediction

1 code implementation • 9 Nov 2023 • Julia Briden, Trey Gurga, Breanna Johnson, Abhishek Cauligi, Richard Linares

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.

Computational Efficiency Time Series