Existing methods for reconstructing interactive scenes primarily focus on replacing reconstructed objects with CAD models retrieved from a limited database, resulting in significant discrepancies between the reconstructed and observed scenes. To address this issue, our work introduces a part-level reconstruction approach that reassembles objects using primitive shapes. This enables us to precisely replicate the observed physical scenes and simulate robot interactions with both rigid and articulated objects. By segmenting reconstructed objects into semantic parts and aligning primitive shapes to these parts, we assemble them as CAD models while estimating kinematic relations, including parent-child contact relations, joint types, and parameters. Specifically, we derive the optimal primitive alignment by solving a series of optimization problems, and estimate kinematic relations based on part semantics and geometry. Our experiments demonstrate that part-level scene reconstruction outperforms object-level reconstruction by accurately capturing finer details and improving precision. These reconstructed part-level interactive scenes provide valuable kinematic information for various robotic applications; we showcase the feasibility of certifying mobile manipulation planning in these interactive scenes before executing tasks in the physical world.

翻译：现有交互场景重建方法主要依赖于从有限数据库中检索CAD模型来替换重建对象，导致重建场景与观测场景之间存在显著差异。为解决这一问题，本文提出了一种基于原始几何体进行部件级对象装配重建的方法，能够精确复现观测到的物理场景，并支持机器人与刚体及铰接对象的交互模拟。通过将重建对象分割为语义部件，并将原始几何体与这些部件对齐，我们将其装配为CAD模型，同时估算运动学关系，包括父子接触关系、关节类型及参数。具体而言，通过求解系列优化问题获得最优原始几何体对齐方案，并基于部件语义与几何特性估算运动学关系。实验表明，部件级场景重建通过精准捕捉细节信息与提升精度，性能显著优于对象级重建。这些重建的部件级交互场景为多种机器人应用提供了关键运动学信息；我们验证了在物理世界执行任务前，可借助此类交互场景验证移动操作规划的可行性。