Event Location: GHC 4405

Abstract: Future in-situ resource utilization promises to enable affordable exploration of space and extend human presence in the Solar System by minimizing the materials that must be carried from Earth. This is predicated on the existence of economic quantities of native materials that can be converted into consumable resources, such as water, oxygen, and fuel. Early investigative missions will explore the poles of planetary bodies, including the Moon and Mercury, to characterize and quantify water ice and other volatiles prevalent there. Solar-powered rovers provide a viable means of polar exploration but require abundant sunlight along their route to retain power and heat. The dynamic nature of polar lighting complicates this constraint and makes planning extended traverses challenging. Stationary rovers are limited to half of a diurnal cycle of reliable operation, but close proximity to a pole affords the opportunity to drive with the Sun to prolong exploration by an order of magnitude or more.

This research has demonstrated that there exist temporal routes near the poles of the Moon that provide months of uninterrupted sunlight, Earth visibility for communication, and shallow slopes attainable at moderate speeds. Prolonged traverses like these represent substantial value added compared to more conservative mission designs that end after lingering at a single locale for 8-12 Earth days. The ability to automatically identify such routes from remote sensing data and plan safe, reliable traverses will ensure that mission requirements are met and enable science objectives that dramatically expand the scope of polar exploration. Ongoing research seeks to develop planning methods that fully realize these benefits.

To maximize impact, polar traverse planners must take full advantage of the highest-resolution data available over global ranges, effectively utilize both solar power and stored battery power for arbitrary solar panel configurations, enforce global constraints on stored energy and thermal state, enhance routes on the basis of mission objectives, and demonstrate robustness to terrain map error and unanticipated obstacles. Adding these dimensions and capabilities to grid-based, deterministic planners introduces problems of tractability. This research will therefore emphasize the development of a sampling-based, asymptotically optimal planner based on the recent Informed RRT* algorithm. Challenges will include incorporating heterogeneous state dimensions and constraints while preserving guarantees on completeness and optimality, satisfying mission requirements and science objectives, and developing heuristics to improve traverse robustness. Planning methods will be tested against baseline deterministic implementations to evaluate algorithm performance and solution quality.

Additional contributions sought by this research include incorporation of mixed-initiative human input and identification of minimum viable multiyear routes.

Committee:William “Red” Whittaker, Co-chair

David Wettergreen, Co-chair

Alonzo Kelly

Paul Tompkins, SpaceX

Anthony Colaprete, NASA