Autonomous Asteroid Characterization through Nanosatellite Swarming

This paper develops a novel algorithmic framework for autonomous asteroid characterization for the Autonomous Nanosatellite Swarming (ANS) mission concept. There is significant interest in asteroids as evidenced by multiple completed and ongoing asteroid missions. However, these missions heavily rely on human oversight and Earth-based resources such as the NASA Deep Space Network. Such an approach is not sustainable in the long term due to cost and oversubscribed Earth-based resources. Furthermore, these missions typically utilize a single spacecraft that is slow to adapt to its environment due to light time delay and gaps in communication with the Earth. In contrast, ANS comprises multiple small spacecraft that operate autonomously after a brief ground-in-the-loop initialization. The spacecraft are equipped with low size, weight, power, and cost (SWaP-C) avionics including star trackers, short-range cameras, radio-frequency intersatellite links, and chip scale atomic clocks. The algorithmic framework developed in this paper utilizes the intersatellite links and images of the asteroid to simultaneously estimate the spacecraft states as well as the asteroid gravity field, shape, and rotational motion. This class of estimation problem is defined in this paper as simultaneous navigation and characterization (SNAC), which is a superset of simultaneous localization and mapping. The ANS SNAC framework consists of three novel modules: 1) multi-agent optical landmark tracking and 3D point reconstruction using stereovision, 2) state estimation through a computationally efficient and robust unscented Kalman filter, and 3) reconstruction of a global spherical harmonic shape model by leveraging a priori knowledge of the shape properties of small celestial bodies. This new framework is validated through the numerical simulation of three spacecraft orbiting the asteroid 433 Eros. The simulation results demonstrate that the proposed architecture provides autonomous and accurate SNAC in a safe manner without any a priori shape model and using only low SWaP-C avionics.