AI in space: applications examples and challenges
Gianluca Furano, Antonis Tavoularis, Marco Rovatti
Abstract
While AI is being successfully applied in space (e.g. in the areas of enhanced monitoring and diagnostics, in prediction, image analysis etc.), it is still not applied on-board.Many potential applications could benefit from AI on-board capabilities at different levels. Probably the most straightforward approach is the use of AI for remote sensing missions at payload processing level to perform image processing tasks. Nevertheless, other applications at instrument, satellite or system levels could also represent important breakthroughs in the way we use and operate satellites for any kind of mission.A possible way forward would be to train machine learning models on-ground, up-link the trained models and use them on-board. This would enable an increased level of autonomy (e.g. opportunistic science) and added-value on-board, for a little extra computational cost. Even the most computational intensive AI models (e.g. deep learning) have now versions that allow trained models to be run on smartphones (“on the edge”).