New mining and exploration projects have revived across Europe with an increasing demand for critical raw materials driven by the energy transition and unstable political conditions. Hyperspectral imaging proves to be an excellent tool for quick and efficient non-invasive mineral exploration. By mounting hyperspectral- and LiDAR sensors on drones and other robots, inaccessible and dangerous areas can safely be mapped for geological information. With increasingly deeper and more hazardous underground mines, a robot-aided hyperspectral mineral exploration method in underground environments is needed. This study configures a Cubert X20P hyperspectral camera (VNIR) and VLP16 LiDAR on the versatile Boston Dynamics Spot robot, creating a multi-sensor robotic platform for data acquisition in underground mining environments. A data workflow is proposed and applied to the granite greisen rocks of the Zinnwald/Cinnovec mine (Germany). Combining hyperspectral and geometric data provides unique 3D hypercloud results interpreted for mineral and structural features. Hyperspectral analysis successfully identifies iron and clay minerals along with multiple vein and fault structures. A remote mineral exploration method in underground mines significantly improves safety by keeping the operator away from hazardous areas. The proposed platform and workflow show potential to contribute to underground mineral exploration, especially if future improvements in data quality and autonomous capabilities are made.

The growing importance of rare earth elements (REEs) in sustainable technologies necessitates anefficient assessment of potential resource targets within the European Union. Traditional analyticaltechniques for REE determination have drawbacks like destructive and time-consuming samplepreparation, but hyperspectral imaging (HSI) and laser-induced fluorescence (LiF) offer promisingalternatives. This project aims to use a combined HSI and LiF method to qualitatively characterizeREE mineralization and alteration in drill core samples from the Storkwitz deposit, Germany. The goal is to develop a transferrable mapping approach for REEs, while enhancing our understanding of the Storkwitz deposit. It aims to check the robustness of HSI conducted across the extendedwavelength range as a tool in effectively characterizing the lithologies associated with REEmineralization in the Storkwitz breccia. It also tests if the combined HSI-LiF can provide newinsights into the presence of REEs and its associated minerals in the Storkwitz breccia.The proposed workflow involves acquiring hyperspectral data of the Storkwitz drill core and blocksections in three wavelength ranges (VNIR-SWIR, MWIR, and LWIR). Automatic and manualendmember extraction is performed on the smaller subsection of data to create spectral libraries,which are then used for spectral unmixing and mapping of the entire hyperspectral dataset toidentify lithologies. LiF is used to identify and map rare earth elements (REEs) in selected REErichzones identified from the hyperspectral data.The results indicated that the Storkwitz Breccia is primarily composed of ankerite in the matrix,along with minor amounts of white mica, clay, iron oxides, and REE-fluorcarbonates. The brecciacontains different clasts, including granitoid clasts rich in orthoclase and quartz-albite-biotite, aswell as carbonatitic clasts dominated by ankerite, dolomite, and ankerite-calcite. The breccia alsounderwent four alteration phases, including fenitization, biotite alteration, white mica-clayalteration, and ferric alteration. Laser-induced spectroscopy confirmed the presence of REEs, withapatite and REE-fluorcarbonates, particularly bastnäsite, being the main REE-bearing minerals.The specific REEs identified include Nd3+, Sm3+, Pr3+, and possibly Eu3+. The comprehensiveworkflow combining hyperspectral imaging and laser-induced fluorescence spectroscopy provedto be a successful approach for characterizing lithologies and mapping rare earth elementmineralization in the Storkwitz breccia. The study opens up new possibilities for efficient REEexploration in similar geological settings, providing valuable information for geological loggingand interpretation.