Machine Learning in Space: Surveying the Robustness of on-board ML models to Radiation

arXiv:2405.02642v1 Announce Type: new
Abstract: Modern spacecraft are increasingly relying on machine learning (ML). However, physical equipment in space is subject to various natural hazards, such as radiation, which may inhibit the correct operation of computing devices. Despite plenty of evidence showing the damage that naturally-induced faults can cause to ML-related hardware, we observe that the effects of radiation on ML models for space applications are not well-studied. This is a problem: without understanding how ML models are affected by …

abstract arxiv board computing cs.lg devices equipment evidence hazards however machine machine learning ml models modern natural robustness space spacecraft type