10 citations · 12 across the 10 of their papers we have counts for
11 papers
Reachability-Informed Reinforcement Learning for Multi-Impulse Interplanetary Transfers
Yashdeep Chaudhary, Roberto Armellin, Harry Holt
Reinforcement learning offers the prospect of a reusable sequential decision-making mechanism for spacecraft trajectory design, motivating policy interfaces that connect learned de…
Distribution-Agnostic Robust Trajectory Optimization via Chance-Constrained Reinforcement Learning
Yashdeep Chaudhary, Roberto Armellin, Harry Holt +1
This paper presents a distribution-agnostic robust trajectory-optimization framework based on chance-constrained reinforcement learning. The uncertainty is represented here through…
Using the Translation Theorem for the Automated Stationkeeping of Extremely-Low Lunar Missions
Jack Yarndley, Martin Lara, Harry Holt +1
Extremely-Low Lunar Orbits (eLLOs) (altitudes km) exhibit severe perturbations due to the highly non-spherical lunar gravitational field, presenting unique challenges to…
Learning-Based Stable Optimal Guidance for Spacecraft Close-Proximity Operations
Kun Wang, Roberto Armellin, Adam Evans +2
Machine learning techniques have demonstrated their effectiveness in achieving autonomy and optimality for nonlinear and high-dimensional dynamical systems. However, traditional bl…
GTOC 12: Results from TheAntipodes
Roberto Armellin, Andrea Bellome, Xiaoyu Fu +4
We present the solution approach developed by the team `TheAntipodes' during the 12th edition of the Global Trajectory Optimization Competition (GTOC 12). An overview of the approa…
Multi-Target Spacecraft Mission Design using Convex Optimization and Binary Integer Programming
Jack Yarndley, Harry Holt, Roberto Armellin
The optimal design of multi-target rendezvous and flyby missions is challenging due to the combination of traditional spacecraft trajectory optimization and high-dimensional combin…
Trajectory Design and Guidance for Far-range Proximity Operations of Active Debris Removal Missions with Angles-only Navigation and Safety Considerations
Minduli C. Wijayatunga, Roberto Armellin, Harry Holt
Observability of the target, safety, and robustness are often recognized as critical factors in ensuring successful far-range proximity operations. The application of angles-only (…
Convex Optimization-based Model Predictive Control for Active Space Debris Removal Mission Guidance
Minduli Wijayatunga, Roberto Armellin, Harry Holt +2
A convex optimization-based model predictive control (MPC) algorithm for the guidance of active debris removal (ADR) missions is proposed in this work. A high-accuracy reference fo…
Convex Optimization-Based Model Predictive Control for the Guidance of Active Debris Removal Transfers
Minduli Wijayatunga, Roberto Armellin, Harry Holt +2
Active debris removal (ADR) missions have garnered significant interest as means of mitigating collision risks in space. This work proposes a convex optimization-based model predic…
Design and Guidance of a Multi-Active Debris Removal Mission
Minduli Wijayatunga, Roberto Armellin, Harry Holt +2
Space debris have been becoming exceedingly dangerous over the years as the number of objects in orbit continues to rise. Active debris removal (ADR) missions have garnered signifi…
Team theAntipodes: Solution Methodology for GTOC11
Roberto Armellin, Laurent Beauregard, Andrea Bellome +7
This paper presents the solution approach developed by the team "theAntipodes" for the 11th Global Trajectory Optimization Competition (GTOC11). The approach consists of four main…