Predicted conjunction between Aeolus and Starlink 44 satellites. (Credit: ESA)
PARIS (ESA PR) — ESA is challenging machine learning experts to help forecast and prevent collisions in space. The Agency’s Advanced Concepts Team and Space Debris Office have come together to set up the latest in a series of AI-themed competitions based on actual space data.
Space is not as empty as it used to be. More than 34 000 items of space debris bigger than 10 cm are orbiting our planet. Of those, some 22 300 items are being regularly tracked by the telescopes and powerful radars of the US Space Surveillance Network and their trajectories maintained in a catalogue.
In highly-trafficked orbits, active collision avoidance has become a routine task in space operations. Space surveillance data reveal potential risks for satellites to collide with another space object at multiple kilometres per second – whether from active missions or space debris.
For a typical satellite in low-Earth orbit, hundreds of alerts are issued weekly, in the form of ‘conjunction data messages’. After automatic processing and filtering most of these are found to be low-risk, but that still leaves about two actionable alerts per mission per week, requiring detailed examination ...