8 citations · 9 across the 5 of their papers we have counts for
5 papers
Transfer Learning of Multiobjective Indirect Low-Thrust Trajectories Using Diffusion Models and Markov Chain Monte Carlo
Jannik Graebner, Ryne Beeson
Preliminary low-thrust spacecraft mission design is a global search problem characterized by a complex solution landscape, multiple objectives, and numerous local minima. During th…
Gradient-Informed Monte Carlo Fine-Tuning of Diffusion Models for Low-Thrust Trajectory Design
Jannik Graebner, Ryne Beeson
Preliminary mission design of low-thrust spacecraft trajectories in the Circular Restricted Three-Body Problem is a global search characterized by a complex objective landscape and…
Self-supervised diffusion model fine-tuning for costate initialization using Markov chain Monte Carlo
Jannik Graebner, Ryne Beeson
Global search and optimization of long-duration, low-thrust spacecraft trajectories with the indirect method is challenging due to a complex solution space and the difficulty of ge…
Global Search for Optimal Low Thrust Spacecraft Trajectories using Diffusion Models and the Indirect Method
Jannik Graebner, Ryne Beeson
Long time-duration low-thrust nonlinear optimal spacecraft trajectory global search is a computationally and time expensive problem characterized by clustering patterns in locally…
Learning Optimal Control and Dynamical Structure of Global Trajectory Search Problems with Diffusion Models
Jannik Graebner, Anjian Li, Amlan Sinha +1
Spacecraft trajectory design is a global search problem, where previous work has revealed specific solution structures that can be captured with data-driven methods. This paper exp…