Regolith lntelligence: ISRU Prepping with machine learning research on lunar rocks

Basic data for this project

Description

Understanding the local-scale nature and evolution of the lunar regolith, at the surface and near-subsurface, is crucial for a variety of aspects: from the accumulation and preservation of volatiles, to planning and performing landing, roving and sampling operations, to in situ ressources utilizations. The novelty of the proposed research is to couple an automatic detection and characterization of boulders at the global scale with the new boulder models and with thermal data. This coupling will enable to answer a variety of key questions concerning the lunar regolith nature and evolution. We will understand subsurface regolith properties and thus volatile presence. This research will directly strength the investigations carried out by ESA on and around the Moon, like the ESA Prospect project.