标题： ArtGS：用于关节物体交互式视觉-物理建模与操作的3D高斯泼溅 显示英文标题

标题： ArtGS:3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects

摘要： 由于复杂的运动学约束和现有方法的物理推理能力有限，铰接物体操作仍然是机器人领域的关键挑战。 在本工作中，我们引入了ArtGS，这是一种新颖的框架，通过整合视觉-物理建模来扩展3D高斯点云（3DGS），以实现对铰接物体的理解和交互。 ArtGS从多视角RGB-D重建开始，随后使用视觉-语言模型（VLM）进行推理，以提取语义和结构信息，特别是铰接骨骼。 通过动态、可微分的基于3DGS的渲染，ArtGS优化铰接骨骼的参数，确保物理上一致的运动约束并增强操作策略。 通过利用动态高斯点云、跨身体适应性和闭环优化，ArtGS建立了一个高效、可扩展且通用的铰接物体建模和操作新框架。 在仿真和现实环境中的实验表明，ArtGS在各种铰接物体的关节估计准确性和操作成功率方面显著优于先前方法。 附加图片和视频可在项目网站上查看：https://sites.google.com/view/artgs/home 显示英文摘要

摘要： Articulated object manipulation remains a critical challenge in robotics due to the complex kinematic constraints and the limited physical reasoning of existing methods. In this work, we introduce ArtGS, a novel framework that extends 3D Gaussian Splatting (3DGS) by integrating visual-physical modeling for articulated object understanding and interaction. ArtGS begins with multi-view RGB-D reconstruction, followed by reasoning with a vision-language model (VLM) to extract semantic and structural information, particularly the articulated bones. Through dynamic, differentiable 3DGS-based rendering, ArtGS optimizes the parameters of the articulated bones, ensuring physically consistent motion constraints and enhancing the manipulation policy. By leveraging dynamic Gaussian splatting, cross-embodiment adaptability, and closed-loop optimization, ArtGS establishes a new framework for efficient, scalable, and generalizable articulated object modeling and manipulation. Experiments conducted in both simulation and real-world environments demonstrate that ArtGS significantly outperforms previous methods in joint estimation accuracy and manipulation success rates across a variety of articulated objects. Additional images and videos are available on the project website: https://sites.google.com/view/artgs/home