用真实火星影像生成可控光照的空中视角，解决火星视觉导航数据少的问题。
MARTIAN: A Rendering Framework for Aerial Mars Imagery from HiRISE Orbital Data
- 基于真实HiRISE地图用Blender渲染火星地形，支持不同高度和光照条件
- 生成带精确位姿标注的合成图像，可用于训练视觉导航模型
- 已验证可用于无人机定位系统，适合火星探测器视觉算法研究者
火星空中导航依赖于对多变光照和地形形态具有鲁棒性的视觉算法，但其训练与评估面临大规模、标注齐全的空中数据集稀缺的瓶颈。本文提出MARTIAN，一个基于Blender的开源渲染框架，利用真实的HiRISE轨道地图产品，合成在可控光照条件和不同高度下的逼真火星地形空中视图。该框架生成带有准确位姿标注的观测数据，直接缓解了火星视觉导航训练数据不足的问题。通过在Ingenuity及未来火星旋翼飞行器的地图匹配定位系统中的部署验证，采用合成数据训练的深度图像匹配器成功在真实火星影像上表现良好。MARTIAN已在GitHub公开：https://github.com/nasa-jpl/martian。
原文摘要 · Abstract (English)
Aerial navigation on Mars requires vision-based pipelines that are robust to the diverse illumination conditions and terrain morphology of the Martian surface. A key bottleneck for training and evaluating such methods is the scarcity of large-scale, annotated aerial datasets. We present MARTIAN, an open-source Blender-based rendering framework that leverages real HiRISE orbital map products to synthesize realistic aerial views of the Martian terrain under controllable lighting conditions and at varying altitudes. MARTIAN generates observations with accurate pose annotations, directly addressing the scarcity of training data for vision-based navigation on Mars. The framework has been validated through its deployment in concurrent work on map-based localization systems for Ingenuity and future Mars rotorcraft, where synthetically trained deep image matchers were successfully evaluated on real Mars imagery. MARTIAN is publicly available at: https://github.com/nasa-jpl/martian.
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