8 citations · 16 across the 17 of their papers we have counts for
18 papers
A Probabilistic Modeling Framework for Transient Debris Outcomes in Low Lunar Orbits
Arjun Chhabra, Ryne Beeson
This work presents a novel probabilistic framework for the assessment of orbital debris fragment outcomes in the low lunar orbit (LLO) regime over time horizons ranging from a few…
Diffusion-Based Multiple-Shooting Indirect Optimal Control for Fuel-Optimal Spacecraft Trajectory Generation
Saeid Tafazzol, Ehsan Taheri, Ryne Beeson
Diffusion-based generative models (DMs) have found applications in control problems, and in particular robotics, where the DMs enable exploration of possible control solutions. A c…
Complexity Bounds and Approaches to Learning Projected Gradient Descent Solver Iterates
Anjian Li, Ryne Beeson
Data scarcity poses a fundamental challenge in training generative models to produce initial guesses for parametric optimization problems that are otherwise numerically expensive t…
GLENS: Global Search via Learning from Solver Iterates with Diffusion Models
Anjian Li, Bartolomeo Stellato, Ryne Beeson
We consider the problem of generating a large collection of initial guesses for local minima of multimodal non-convex continuous optimization problems. The goal is for these initia…
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…
Bi-Level Optimal Control Framework For Missed-Thrust-Design With First-Order Bounds On Maximum Missed-Thrust-Duration
Amlan Sinha, Ryne Beeson
In this paper, we present a bi-level optimal control framework for designing low-thrust spacecraft trajectories with robustness against missed-thrust-events. The upper-level (UL) p…
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…
Aligning Diffusion Model with Problem Constraints for Trajectory Optimization
Anjian Li, Ryne Beeson
Diffusion models have recently emerged as effective generative frameworks for trajectory optimization, capable of producing high-quality and diverse solutions. However, training th…
Predictive Planner for Autonomous Driving with Consistency Models
Anjian Li, Sangjae Bae, David Isele +2
Trajectory prediction and planning are essential for autonomous vehicles to navigate safely and efficiently in dynamic environments. Traditional approaches often treat them separat…
Initial Guess Generation for Low-Thrust Trajectory Design with Robustness to Missed-Thrust-Events
Amlan Sinha, Ryne Beeson
The growing interest in cislunar space exploration in recent years has driven an increasing demand for efficient low-thrust missions to key cislunar orbits. These missions, typical…
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…
Global Search of Optimal Spacecraft Trajectories using Amortization and Deep Generative Models
Ryne Beeson, Anjian Li, Amlan Sinha
Preliminary spacecraft trajectory optimization is a parameter dependent global search problem that aims to provide a set of solutions that are of high quality and diverse. In the c…
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…
Algorithmic Considerations for Effective Global Search of Robust Low-Thrust Trajectories
Amlan Sinha, Ryne Beeson
The growing interest in the cislunar domain over the past decade has led to an increasing demand for low-thrust missions to key orbits within this region. These low-thrust missions…
Statistical Analysis of the Role of Invariant Manifolds on Robust Trajectories
Amlan Sinha, Ryne Beeson
As low-thrust space missions increase in prevalence, it is becoming increasingly important to design robust trajectories against unforeseen thruster outages or missed thrust events…
Constraint-Aware Diffusion Models for Trajectory Optimization
Anjian Li, Zihan Ding, Adji Bousso Dieng +1
The diffusion model has shown success in generating high-quality and diverse solutions to trajectory optimization problems. However, diffusion models with neural networks inevitabl…
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization
Anjian Li, Zihan Ding, Adji Bousso Dieng +1
Optimal trajectory design is computationally expensive for nonlinear and high-dimensional dynamical systems. The challenge arises from the non-convex nature of the optimization pro…