Autonomous Asteroid Characterization Through Nanosatellite Swarming

This paper first defines a class of estimation problem called simultaneous navigation and characterization (SNAC), which is superset localization mapping (SLAM). A SNAC framework then developed for the Autonomous Nanosatellite Swarming (ANS) mission concept to autonomously navigate about characterize an asteroid including gravity field, rotational motion, 3D shape. The ANS consists three modules: 1) multi-agent optical landmark tracking point reconstruction using stereovision, 2) state through computationally efficient robust unscented Kalman filter, 3) spherical harmonic shape model by leveraging priori knowledge properties celestial bodies. Despite significant interest in asteroids, there are several limitations current rendezvous concepts. First, completed missions heavily rely on human oversight Earth-based resources. Second, proposed solutions increase autonomy make oversimplifying assumptions information processing. Third, concepts often opt high size, weight, power, cost (SWaP-C) avionics environmental measurements. Finally, such utilize single spacecraft, neglecting benefits distributed space systems. In contrast, composed multiple autonomous nanosatellites equipped with low SWaP-C avionics. validated numerical simulation spacecraft orbiting 433 Eros. results demonstrate that architecture provides accurate safe manner without only