RigPI: Dynamic Parameter Identification of Rigid Body via VLM-Seeded Differentiable Simulation

arXiv:2606.25212v1 Announce Type: new Abstract: Accurate physical parameter identification of manipulated objects is fundamental to advanced robotic manipulation and the construction of faithful digital twins. However, acquiring physically consistent inertial and frictional properties from real-world interactions remains challenging due to sensing noise, modeling errors, and limited prior knowledge. This paper presents \textbf{RigPI}, a systematic framework for identifying dynamic parameters of ...