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Improving Lunar Map Resolution With AI

Completed TRL 3 (started at 3, targeting 3)

Description

Currently available high resolution lunar maps are 5 m/pixel. These products are derived from LOLA data (https://pgda.gsfc.nasa.gov/products/78). The goal of this project was to take the source data and generate an accurate, higher resolution version of the elevation maps. This should be done for a small region of high interest for future human lunar landing. NASA has established a set of landing locations for evaluation(https://www.nasa.gov/news-release/nasa-identifies-candidate-regions-for-landing-next-americans-on-moon/). The pipeline created should be capable of repeating the same work with additional lunar regions of interest, if successful.

Benefits

Potential use cases for this higher resolution data product include servings as training data sets for neural nets and other algorithms that require lunar maps as inputs. This includes terrain relative navigation, hazard detection and avoidance, crater navigation, simulation visualization, and other tool sets. This work has the potential to positively impact any mission that lands on the Moon, operates on the Moon, or uses the Moon for navigation. This includes CLPS, HLS, Gateway, and EHP. An additional potential use case is the broad availability of lunar terrain data sets for use in academic/university navigation R&D.

Details

Technology areaExploration Destination Systems > In Situ Resource Use > Destination Resource Exploration
ProgramPrizes, Challenges, and Crowdsourcing (PCC)
Lead organizationJohnson Space Center, Houston, TX
Start date2024-06-01
End date2025-02-28

Project contacts

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How to get involved

This is early/mid-stage (TRL 3) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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