Terrain Relative Navigation for Lunar Polar Roving: Exploiting Geometry, Shadows, and Planning FangEugene 2020 <div>Water ice at the lunar poles could be the most valuable resource beyond planet Earth. However, that value is not foregone, and can only be determined by rovers that evaluate the distributions of abundance, concentration, and characteristics of this ice. The near-term explorations will be solar and unlikely to endure night and hence are limited to a single cycle of lunar daylight. Sun-synchronous polar routes promise order-of-magnitude greater duration and</div><div>range. Such routes are, however, brittle in the sense that a rover must be at precisely scheduled time and place. Methods for terrain-based localization that work</div><div>at low latitudes are challenged at the lunar poles, where the grazing sunlight casts long shadows that obscure and change views over time. Moreover, the cadence of</div><div>exploration driven by the clocking sun requires terrain localization to be highly informative. Technologies in these areas are lacking, which results in a level of risk that currently makes these missions not viable. This thesis develops methods for terrain relative navigation that enable the robust execution of sun-synchronous routes at the lunar poles. This research advances terrain registration under sensor and map uncertainty, exploits shadows as features for localization, and develops planning algorithms that increase information gain from terrain registration.</div><div>There are four major contributions of this research. The first is a scan matching algorithm that probabilistically geometrically registers rover perspective stereo</div><div>images to a digital elevation map which is evaluated against priors in both simulated and real small-scale experiments. The second is an extension of the geometric method to exploit shadows as features. The third is a method of predicting the uncertainty of terrain-based localization given terrain geometry and lighting. The fourth is a belief space planning algorithm that maximizes the probability of surviving sunsynchronous exploration by considering when and where to perform terrain relative corrections. Together, these methods are evaluated for route robustness and mission risk within the developed simulation framework and with scale field data. The work developed in this thesis enables robust sun-synchronous routes for multi-month exploration and increased science return at the lunar poles.</div>