Learning Optimal Control and Dynamical Structure of Global Trajectory Search Problems with Diffusion Models
On the map: Diffusion models → Diffusion and flow policies for robotics
Abstract (arXiv)
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 explores two global search problems in the circular restricted three-body problem: hybrid cost function of minimum fuel/time-of-flight and transfers to energy-dependent invariant manifolds. These problems display a fundamental structure either in the optimal control profile or the use of dynamical structures. We build on our prior generative machine learning framework to apply diffusion models to learn the conditional probability distribution of the search problem and analyze the model's capability to capture these structures.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 5 of its 27 references that are in the map. First posted on arXiv 3 Oct 2024.
Builds on
5 of 27 references.
References · 5
- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
- 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
- 2022Classifier-Free Diffusion Guidancecited by 5,847
- 2023Amortized Global Search for Efficient Preliminary Trajectory Design with Deep Generative Modelscited by 12
Built on by
Citing papers per year: 2025: 4; 2026: 2.
6 papers.
- 2025Global Search for Optimal Low Thrust Spacecraft Trajectories using Diffusion Models and the Indirect Methodcited by 8
- 2025Aligning Diffusion Model with Problem Constraints for Trajectory Optimizationcited by 7
- 2025Self-supervised diffusion model fine-tuning for costate initialization using Markov chain Monte Carlocited by 1
- 2025Gradient-Informed Monte Carlo Fine-Tuning of Diffusion Models for Low-Thrust Trajectory Designcited by 1
- 2026Transfer Learning of Multiobjective Indirect Low-Thrust Trajectories Using Diffusion Models and Markov Chain Monte Carlocited by 1
- 2026GLENS: Global Search via Learning from Solver Iterates with Diffusion Modelscited by 1
- 2026GLENS: Global Search via Learning from Solver Iterates with Diffusion Models29 May 2026
- 2026Transfer Learning of Multiobjective Indirect Low-Thrust Trajectories Using Diffusion Models and Markov Chain Monte Carlo9 May 2026
- 2025Gradient-Informed Monte Carlo Fine-Tuning of Diffusion Models for Low-Thrust Trajectory Design9 Dec 2025
- 2025Self-supervised diffusion model fine-tuning for costate initialization using Markov chain Monte Carlo2 Oct 2025
- 2025Aligning Diffusion Model with Problem Constraints for Trajectory Optimization1 Apr 2025
- 2025Global Search for Optimal Low Thrust Spacecraft Trajectories using Diffusion Models and the Indirect Method13 Jan 2025
Similar, not cited
Close in wording, no citation either way
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- 2026Diffusion-Based Multiple-Shooting Indirect Optimal Control for Fuel-Optimal Spacecraft Trajectory Generation
- 2026Spacecraft Rendezvous Trajectory Generation with Modular Constraints via Diffusion Model Composition
- 2024DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization
- 2024Diffusion Models for Generating Ballistic Spacecraft Trajectories
- 2026Accelerating trajectory optimization with Sobolev-trained diffusion policies
- 2019Learning Dynamic-Objective Policies from a Class of Optimal Trajectories
- 2025Multi-Phase Spacecraft Trajectory Optimization via Transformer-Based Reinforcement Learning