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arXiv · 2202.06617

An Application of Online Learning to Spacecraft Memory Dump Optimization

Tommaso Cesari·Jonathan Pergoli·Michele Maestrini·Pierluigi Di Lizia
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Abstract

In this paper, we present a real-world application of online learning with expert advice to the field of Space Operations, testing our theory on real-life data coming from the Copernicus Sentinel-6 satellite. We show that in Spacecraft Memory Dump Optimization, a lightweight Follow-The-Leader algorithm leads to an increase in performance of over $60\%$ when compared to traditional techniques.

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Tommaso Cesari, Jonathan Pergoli, Michele Maestrini, Pierluigi Di Lizia. 2022-02-14. An Application of Online Learning to Spacecraft Memory Dump Optimization. https://arxiv.org/abs/2202.06617

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