Future short or long-term space missions require a new generation of monitoring and diagnostic systems due to communication impasses as well as limitations in specialized crew and equipment. Machine learning supported diagnostic systems present a viable solution for medical and technical applications. We discuss challenges and applicability of such systems in light of upcoming missions and outline an example use case for a next-generation medical diagnostic system for future space operations. Additionally, we present approach recommendations and constraints for the successful generation and use of machine learning models aboard a spacecraft.
@article{arxiv.2106.05659,
title = {Next-Gen Machine Learning Supported Diagnostic Systems for Spacecraft},
author = {Athanasios Vlontzos and Gabriel Sutherland and Siddha Ganju and Frank Soboczenski},
journal= {arXiv preprint arXiv:2106.05659},
year = {2021}
}
Comments
Accepted in the AI for Spacecraft Longevity Workshop at IJCAI2021