ABot-Earth 0.5：生成式三维地球模型

摘要

我们提出了ABot-Earth 0.5，这是一个生成式3D框架，旨在从普遍存在的地理参考卫星图像中合成广阔、无缝的3D环境。为此，我们提出了一种直接基于3D高斯泼溅（3DGS）表示构建的新型生成模型。该模型在多样化的真实世界城市重建语料库上进行训练，学习生成逼真的几何形状和纹理。在推理阶段，它仅以卫星图像为条件，以每平方公里不到10分钟的可扩展速率合成新颖的3D场景，同时展现出卓越的真实感。该框架的设计注重可访问性，集成了分层细节层次（LOD）结构，允许在基于网络的地图引擎上进行实时的交互式可视化。这个高保真模拟沙盒有效弥合了仿真到真实的领域差距，支持关键的具身人工智能下游应用，如闭环无人机导航。通过提供超低成本和高效的解决方案，ABot-Earth 0.5显著降低了大规模3D重建的技术和财务障碍，并赋能全球数字地球可视化的未来。

English

We present ABot-Earth 0.5, a generative 3D framework designed to synthesize vast, seamless 3D environments from ubiquitous, geospatially referenced satellite imagery. To achieve this, we propose a novel generative model formulated directly with the 3D Gaussian Splatting (3DGS) representation. The model is trained on a diverse corpus of existing real-world urban reconstructions, learning to generate realistic geometry and textures. At inference, it synthesizes novel 3D scenes conditioned solely on satellite imagery at a scalable rate of under 10 minutes per square kilometer, while demonstrating exceptional realism. The framework is designed for accessibility, with integrated hierarchical level-of-detail (LOD) structures that permit real-time, interactive visualization on web-based map engines. This high-fidelity simulation sandbox effectively mitigates the sim-to-real domain gap, enabling critical downstream Embodied AI applications like closed-loop UAV navigation. By providing an ultra-low-cost and high-efficiency solution, ABot-Earth 0.5 significantly lowers the technical and financial barriers to large-scale 3D reconstruction and empowers the future of global digital earth visualization.