Abstract
Artificial Intelligence (AI) techniques are being used in general-purpose industrial computing systems. There is a great interest in expanding its use across other types of systems. However, they are not immediately applicable to embedded safety-critical systems. In particular, in spacecrafts, there are subsystems with high integrity requirements, which means that their failure could affect the overall behavior of the vehicle or even the loss of the complete mission. This paper deals with the use of some relevant AI techniques onboard space systems. Machine Learning and Neural Networks are potential techniques for these systems. The objective of this paper is to evaluate its applicability, select the most appropriate tools, and determine its feasibility to place onboard the satellite. Through the analysis of standards proposals, and a thermal estimation use case, we identify the issues, challenges, and guidelines to be considered for the use of AI, specifically machine learning, in UPMSat-3.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
