通过时间几何约束实现可泛化的关节物体重建
REArtGS++: Generalizable Articulation Reconstruction with Temporal Geometry Constraint via Planar Gaussian Splatting
- 用平面高斯泼溅建模关节运动，解耦螺栓类动作
- 在真实与合成数据上均提升表面重建与参数估计精度
- 适合需要泛化到未知状态的机器人抓取与逆向设计
关节物体广泛存在于日常环境中，如抽屉和冰箱。针对其部件级表面重建与关节参数估计问题，REArtGS提出一种无需类别先验的方法，利用双状态多视角RGB图像进行建模。然而我们发现，现有方法仍难以处理螺栓关节或多重部件物体，且缺乏对未见状态的几何约束。本文提出REArtGS++，一种结合时间几何约束与平面高斯泼溅的可泛化关节物体重建新方法。首先，对每个关节建模解耦的螺栓运动，无需类型先验；通过部件运动融合联合优化部件感知高斯与关节参数。为引入连续时间几何约束，强制高斯点保持平面性，并基于泰勒一阶展开建立平面法向与深度间的时序一致性正则化。在合成与真实世界关节物体上的大量实验表明，本方法在可泛化部件级表面重建与关节参数估计方面显著优于现有方法。
原文摘要 · Abstract (English)
Articulated objects are pervasive in daily environments, such as drawers and refrigerators. Towards their part-level surface reconstruction and joint parameter estimation, REArtGS introduces a category-agnostic approach using multi-view RGB images at two different states. However, we observe that REArtGS still struggles with screw-joint or multi-part objects and lacks geometric constraints for unseen states. In this paper, we propose REArtGS++, a novel method towards generalizable articulated object reconstruction with temporal geometry constraint and planar Gaussian splatting. We first model a decoupled screw motion for each joint without type prior, and jointly optimize part-aware Gaussians with joint parameters through part motion blending. To introduce time-continuous geometric constraint for articulated modeling, we encourage Gaussians to be planar and propose a temporally consistent regularization between planar normal and depth through Taylor first-order expansion. Extensive experiments on both synthetic and real-world articulated objects demonstrate our superiority in generalizable part-level surface reconstruction and joint parameter estimation, compared to existing approaches. Project Site: https://sites.google.com/view/reartgs2/home.
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