10 citations · 12 across the 15 of their papers we have counts for
16 papers
DreamSat-Bench: Development and Initial Testing of a Testbed for AI-Based Pose Estimation from 3D Reconstruction
Alex Posadas-Nava, August Berne, Giovanni Lavezzi +8
This paper presents the development and initial testing of DreamSat-Bench, a modular rendezvous and proximity operation testbed designed to benchmark AI-based relative navigation t…
Exoplanetary Tour Design with Solar Sails: TheAntipodes Results in the GTOC13 Problem
Jack Yarndley, Adam Evans, Xingyu Zhou +2
Solar sails present an attractive but challenging propulsion method for large-scale, long-duration trajectory design problems. In 2025, the 13th Global Trajectory Optimization Comp…
DreamSat-Pose: Spacecraft Pose Estimation from Single-View 3D Reconstructions and Learned 2D-3D Feature Matching
Josiane Uwumukiza, Jocelyn Zhao, Giovanni Lavezzi +5
6-DoF pose estimation is a critical task in autonomous rendezvous and proximity operations. In the case of an unknown target, this task becomes challenging as it shall be paired wi…
Memory-Efficient Meta-Reinforcement Learning for Adaptive Safety-Critical Control in Adversarial Spacecraft Proximity Operations
Alejandro Posadas-Nava, Richard Linares, Minduli Wijayatunga
Autonomous spacecraft rendezvous and proximity operations (RPO) require controllers that guarantee safety under thrust constraints while minimizing fuel expenditure. Input-constrai…
Tiny Recursive Models for Solving the J2-Perturbed Lambert Problem
Minduli Wijayatunga, Roberto Armellin
This paper presents a fast, recursive neural solver for the J2-perturbed Lambert problem based on Tiny Recursive Models (TRM), termed the TRM-Perturbed Lambert (TRM-PL) model. TRM…
An Autonomous, End-to-End, Convex-Based Framework for Close-Range Rendezvous Trajectory Design and Guidance with Hardware Testbed Validation
Minduli C. Wijayatunga, Julian Guinane, Nathan D. Wallace +1
Autonomous satellite servicing missions must execute close-range rendezvous under stringent safety and operational constraints while remaining computationally tractable for onboard…
Meta-Reinforcement Learning for Robust and Non-greedy Control Barrier Functions in Spacecraft Proximity Operations
Minduli C. Wijayatunga, Richard Linares, Roberto Armellin
Autonomous spacecraft inspection and docking missions require controllers that can guarantee safety under thrust constraints and uncertainty. Input-constrained control barrier func…
Learning Safety-Guaranteed, Non-Greedy Control Barrier Functions Using Reinforcement Learning
Minduli Wijayatunga, Nathan Wallace, Salah Sukkarieh +1
Spacecraft rendezvous and proximity operations (RPO) pose safety risks to high-value assets, so formal safety guarantees are critical. Yet conservative safety controllers can reduc…
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…
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…
An Optimised Satellite Constellation for Forest Fire Detection through Edge Computing
Minduli Wijayatunga, Xiaofeng Wu
The end of 2019 marked a bushfire crisis for Australia that affected more than 100000km2 of land and destroyed more than 2000 houses. Here, we propose a method of in-orbit bushfire…
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…
Exploiting Scaling Constants to Facilitate the Convergence of Indirect Trajectory Optimization Methods
Minduli C. Wijayatunga, Roberto Armellin, Laura Pirovano
This note develops easily applicable techniques that improve the convergence and reduce the computational time of indirect low thrust trajectory optimization when solving fuel- and…