Rover Mobility in a Lunar Analogue Dataset

Planetary surface missions depend on reliable rover traversability across diverse terrain conditions. Accurate prediction of traversability relies on terramechanics, the study of wheel-soil interactions, which links terrain properties to vehicle dynamics. Building and validating terramechanics-based models require high-fidelity datasets that couple specific rover geometries with well-characterized surface topographies, yet such datasets remain sparse or incomplete. This paper presents a streamlined experimental pipeline for generating and disseminating comprehensive mobility datasets. We describe our rover, test campaigns, and detail the data-acquisition architecture. Additionally, we release a publicly accessible repository of rover state & action time series, wheel imagery, and terrain scans captured in the Mines Lunar Surface Simulator. The dataset and methodology enable rapid development and validation of traversability metrics, digital twin simulation, and system identification.