ABot-Earth 0.5：生成式3D地球模型

摘要

我們提出了 ABot-Earth 0.5，這是一個生成式 3D 框架，旨在從廣泛存在的地理參考衛星影像中，合成廣闊且無縫的 3D 環境。為達成此目標，我們提出了一種新穎的生成模型，該模型直接以 3D 高斯潑濺（3DGS）表示法來制定。該模型在大量現有真實世界城市重建資料集上進行訓練，學習生成逼真的幾何形狀與紋理。在推理階段，它僅以衛星影像為條件，便能以每平方公里不到 10 分鐘的可擴展速率合成新穎的 3D 場景，同時展現出卓越的真實感。此框架的設計注重可及性，內建了層級式細節層次（LOD）結構，使其能夠在基於網路的地圖引擎上進行即時、互動式的視覺化。這個高擬真的模擬沙盒有效地縮小了模擬到真實的領域差距，從而支援如閉環無人機導航等關鍵的下游具身 AI 應用。透過提供超低成本且高效率的方案，ABot-Earth 0.5 顯著降低了大型 3D 重建的技術與財務門檻，並為全球數位地球視覺化的未來賦能。

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.