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ASAI
An AI copilot for orbital safety that works through collision warnings, tasks sensors when uncertainty is high and proposes a manoeuvre behind a human sign-off.
The problem
Problem: Over 95% of orbital collision alerts are false alarms due to wide tracking uncertainty. Manually analyzing them is too slow, causing operators to waste irreplaceable satellite fuel on unnecessary maneuvers or risk catastrophic crashes.
Who Experiences It: Satellite constellation operators, Flight Dynamics Officers (FDOs), and Space Domain Awareness teams.
How it works
ASAI is an autonomous AI copilot for orbital safety. When an anomaly or collision warning triggers a case, it traverses an Orbital Knowledge Graph, calculates real collision math ( P c P c
), and detects missing evidence. When uncertainty is high, it automatically tasks sensors (radar/optical) to collapse the error margin, re-evaluates the true risk, and presents a defensible action plan with a human-in-the-loop sign-off gate for thruster burns.
How It Solves the Problem: By acting under uncertainty and validating alerts before recommending maneuvers, ASAI eliminates false alarms, saves satellite propellant, and slashes anomaly triage time from hours to seconds.
How Claude was used
Not documented in the submission.
Team
First commit
Individual builders are not listed yet — names are published only with their permission.