Project Overview
Enables spacecraft to autonomously respond to environmental threats and hardware anomalies without waiting for ground intervention, drastically reducing reaction times.
The Problem
The speed of light limits communication with deep space probes. A distress signal from Mars takes up to 22 minutes to reach Earth, and the command to fix it takes another 22 minutes. In critical scenarios, 44 minutes is too long.
Our Solution
An onboard decision engine using reinforcement learning and decision trees. It ingests the output from the anomaly detection models and instantly calculates the optimal sequence of commands to stabilize the spacecraft.
System Architecture
A deterministic state-machine core wrapped in a highly constrained Reinforcement Learning policy network. The engine runs on an isolated, redundant compute node to ensure it remains operational even during primary computer failure.
Impact & Results
Successfully simulated the recovery of a tumbling spacecraft in a frictionless environment in under 3 seconds. Slated for integration into a next-generation asteroid mining probe.