Optical navigation using quadrics and indirect indexing & search methods

Abstract

Autonomy plays a crucial role in navigation to other celestial bodies and around our own planet. With steadily increasing demand for radiometric data on an already strained network, autonomous decision-making is becoming evermore central to spacecraft navigation. Autonomy relies on external sensory data, including digital imagery. While images certainly contain invaluable information, they possess inherent limitations---including scale ambiguities and perspective distortions. Leveraging projective geometry and invariant theory---both vital foundations to computer vision---this work resolves particular questions in navigation by exploiting geometric properties using invariant theory, namely: boundary localization, invariant data storage and interrogation, and pose estimation.