Global Optimization of Low-Thrust Interplanetary Trajectories Using a Machine Learning Surrogate

In this work, we propose a new method to approximate the cost function of Low-Thrust, Multiple-Gravity-Assist interplanetary trajectories using a Machine Learning surrogate. We identified the computation time required to obtain training data as the main limitation when using Machine Learning methods for this purpose so we present a strategy to...

Gaussian process models for preliminary low-thrust trajectory optimization

Low-thrust trajectories can benefit the search for propellant-optimal trajectories, but increases in modeling complexity and computational load remain a challenge for efficient mission design and optimization. In this paper, an approach for developing models utilizing Gaussian Process (GP) regression and classification is proposed to perform...