3 citations · 3 across the 7 of their papers we have counts for
9 papers
GPU-Accelerated Astrodynamics World Models for Spacecraft Rendezvous and Proximity Operations
Duncan Eddy, Isaac R. Ward, Grace Ra Kim +1
World models are an emerging paradigm in representation learning in which an agent jointly learns state-action dynamics and observation models from offline trajectory data, enablin…
Semi-Decentralized Multi-Spacecraft Collision Avoidance under Communication Constraints
Grace Ra Kim, Mahdi Al-Husseini, Duncan Eddy +1
Current spacecraft collision-avoidance operations rely on intermittent ground-station contacts, requiring operators to plan with delayed and asynchronously updated information. Con…
Free-Placement Optimization of Ground Station Locations for Low-Earth Orbit Satellites
Grace Ra Kim, Duncan Eddy, Vedant Srinivas +1
Rapidly expanding low Earth orbit satellite constellations are placing increasing demands on terrestrial ground networks, motivating the development of more efficient ground statio…
Communication-Efficient Learning for Satellite Constellations
Ruxandra-Stefania Tudose, Moritz H. W. Grüss, Grace Ra Kim +2
Satellite constellations in low-Earth orbit are now widespread, enabling positioning, Earth imaging, and communications. In this paper we address the solution of learning problems…
Bringing Federated Learning to Space
Grace Kim, Filip Svoboda, Nicholas Lane
As Low Earth Orbit (LEO) satellite constellations rapidly expand to hundreds and thousands of spacecraft, the need for distributed on-board machine learning becomes critical to add…
Scalable Ground Station Selection for Large LEO Constellations
Grace Ra Kim, Duncan Eddy, Vedant Srinivas +1
Effective ground station selection is critical for low Earth orbiting (LEO) satellite constellations to minimize operational costs, maximize data downlink volume, and reduce commun…
Adaptive Science Operations in Deep Space Missions Using Offline Belief State Planning
Grace Ra Kim, Hailey Warner, Duncan Eddy +4
Deep space missions face extreme communication delays and environmental uncertainty that prevent real-time ground operations. To support autonomous science operations in communicat…
The Measurement Imbalance in Agentic AI Evaluation Undermines Industry Productivity Claims
Kiana Jafari Meimandi, Gabriela Aránguiz-Dias, Grace Ra Kim +3
As industry reports claim agentic AI systems deliver double-digit productivity gains and multi-trillion dollar economic potential, the validity of these claims has become critical…
Space for Improvement: Navigating the Design Space for Federated Learning in Satellite Constellations
Grace Kim, Luca Powell, Filip Svoboda +1
Space has emerged as an exciting new application area for machine learning, with several missions equipping deep learning capabilities on-board spacecraft. Pre-processing satellite…