arXiv:2607.13586cs.CV2026-07

统一物理语义生成3D资产,让机器人模拟更真实。

UniPhysGen: Unified Physical Grounding for Simulation-Ready 3D Assets

论文配图:UniPhysGen: Unified Physical Grounding for Simulation-Ready 3D Assets
图 1 · 摘自论文原文
  • 构建统一框架,自动为3D模型赋予关节与物理属性
  • 在40,000个资产上实现领先性能,支持直接部署于仿真环境
  • 解决几何偏差问题,适用于多样异构3D资产

物理真实的3D资产对具身AI和机器人仿真日益重要。然而,现有3D资产普遍缺乏统一的物理语义,包括关节结构与内在物理属性,难以实现真实交互。当前方法或独立处理这些语义,或依赖标准化物体结构,限制了在异构资产上的鲁棒性。我们提出UniPhys,一个可扩展的框架,可将原始3D资产自动转化为具备统一物理语义的仿真就绪资产。基于此,我们构建了包含40,000个资产的UniPhys-40K数据集,并设计了经严格验证的UniPhys-Bench基准用于统一物理语义评估。进一步提出UniPhysGen,一种联合推理关节语义与内在物理属性的统一模型。该模型引入几何鲁棒的关节定位机制,缓解异构部件分割带来的几何捷径偏差。大量实验表明,其在关节识别与物理属性估计任务中均达到最先进水平,生成的资产可直接用于机器人仿真环境,实现真实物理交互。代码与数据集将公开于https://github.com/breezexian/UniPhysGen。

原文摘要 · Abstract (English)

Physically grounded 3D assets are increasingly important for embodied AI and robotic simulation. However, most existing 3D assets lack unified physical semantics, including articulation semantics and intrinsic physical properties, required for realistic interaction. Current approaches either treat these semantics independently or rely on canonicalized object structures, limiting robustness across heterogeneous 3D assets. We present UniPhys, a scalable framework for automatically transforming raw 3D assets into simulation-ready assets with unified physical semantics. Based on UniPhys, we construct UniPhys-40K, a large-scale physically grounded dataset, together with UniPhys-Bench, a carefully verified benchmark for unified physical grounding evaluation. We further introduce UniPhysGen, a unified physical grounding model that jointly reasons over articulation semantics and intrinsic physical properties. UniPhysGen incorporates geometry-robust articulation grounding to mitigate geometric shortcut bias under heterogeneous part decompositions. Extensive experiments demonstrate state-of-the-art performance across articulation grounding and intrinsic physical property estimation tasks, while the resulting assets can be directly deployed in robotic simulation environments for realistic physical interaction. Our code and dataset will be available at https://github.com/breezexian/UniPhysGen.

3D生成物理模拟机器人统一建模

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