From the 1 of 8 linked papers with an AI index.
8 papers
Semi-Decentralized Multi-Spacecraft Collision Avoidance under Communication Constraints
Grace Ra Kim, Mahdi Al-Husseini, Duncan Eddy +1
The paper presents a semi-decentralized planning framework that models intermittent ground‑station communication as a semi‑decentralized POMDP and computes multi‑spacecraft collisi…
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…
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…
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…