Autonomous On-orbit Object Inspection with Space Sensor Swarms

On-orbit inspection (e.g., detection and classification of space debris) is a critical component of on-orbit service, assembly, and manufacturing (OSAM). U.S. Space Force’s Vice Chief of Space Operations Gen. David Thompson has called on the private sector to help clean up space junk. NASA Orbital Debris Program Office’s R&D strategy prioritizes measuring and indentifying 3mm or smaller debris in low earth orbit (LEO). Commercial space companies want their space assets to preemptively avoid collisions with debris. Current ground-based space sensing infrastructure suffers from poor measurement fidelity due to limited field of view and high latency caused by bent pipe space architecture. Therefore, we propose an inter-connected space sensor swarm system and tasking algorithms that will deliver 10X higher accuracy and 100X lower latency for space object  inspection.  To achieve this R&D goal we will (1) develop dynamical models for the interaction between collaborative sensor swarms and target space objects and (2) develop and test (with UDL data) sensor tip-and-cue tasking algorithms to maximize information gain.