Raúl Castilla-Arquillo, Miguel Olivares-Mendez · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28465 · open-access PDF
月の表面探査は、極端な照明条件下で無構造の地形を感知し、横断しなければならない自律型ローバーにますます依存しています。月の極の近くでは、太陽の低い高さは、ステレオビジョン、地形分割、およびローカライゼーションに挑戦する長い、高コントラストの影を生成します。これらの条件のための感知およびナビゲーションアルゴリズムを開発するには、地面キャンペーンやアナログ施設が高コストでしか提供できない正確な地面真実を備えた大量のセンサーデータが必要です。
Machine translation (Meta M2M100); the English original follows.
Lunar surface exploration increasingly relies on autonomous rovers that must perceive and traverse unstructured terrain under extreme illumination conditions. Near the lunar poles, low sun elevations produce long, high-contrast shadows that challenge stereo vision, terrain segmentation, and localization. Developing perception and navigation algorithms for these conditions requires large amounts of sensor data with accurate ground truth, which field campaigns and analog facilities can only provide at high cost and with limited variety. This paper presents MARE (Modular Autonomy and Rendering En
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