AI and machine learning: Shaking up the space industry

Spacecraft autonomy has been primarily a collection of logic-based algorithms designed to respond to a set of circumstances that can be defined (or at least bounded) a priori. This type of artificial intelligence (AI) has worked well when the inputs to the algorithms fall within the pre-defined mission scope, allowing the pre-built logic statements to generate the appropriate response ahead of time.

Today’s increasingly ambitious mission requirements are demanding higher levels of autonomy and greater navigational precision from spacecraft, requiring more than logic-based AI. High-precision space navigation to small comets and asteroids; entry, descent and landing (EDL) on moons and planets; and, rendezvous and proximity operations (RPO) with both cooperative and uncooperative targets all need sensing and perception capabilities provided by vision-based systems. Traditionally the development of these technologies have fallen within the domain of the public sector, but today the private sector is participating actively by driving progress in vision-based technologies such as autonomous satellite servicing, lunar landing, and research in vision-based AI and machine learning. ..Read more..

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