Dynamic Model Identification and Gravity Compensation for the dVRK-Si Patient Side Manipulator

arXiv:2603.12099v2 Announce Type: replace Abstract: The da Vinci Research Kit (dVRK) has been widely used for research in robot-assisted surgery over the past decade, and its latest generation, the dVRK-Si was made publicly available in 2025. This manuscript presents the first complete kinematic and dynamic modeling framework for the dVRK-Si Patient-Side Manipulator (PSM), whose redesigned mechanism differs substantially from that of the first-generation dVRK and therefore requires a new formulation to accurately capture gravitational effects and improve overall control performance. We first develop a modified DH kinematic model that represents the dVRK-Si PSM's redesigned mechanism. The equations of motion are then derived using the Euler-Lagrange formulation, and the inverse dynamics are expressed in a linear-in-parameters regressor form. The dynamic parameters are identified from data collected along a periodic excitation trajectory optimized for numerical conditioning and estimated by convex optimization subject to the physical feasibility constraints. The identified model is integrated into the dVRK control stack to enable real-time gravity compensation and computed-torque feedforward control. Experiments on a physical dVRK-Si demonstrate that the gravity compensation reduces steady-state joint errors by up to 84% and decreases end-effector tip drift during static holds from 4.2 mm to 0.7 mm. Computed-torque feedforward control further improves transient and trajectory-tracking accuracy. During sinusoidal trajectory tracking, computed-torque feedforward reduces position errors by 35% versus gravity-only feedforward and by 40% versus PID-only. The proposed pipeline could support reliable control, high-fidelity simulation, and learning-based automation on the dVRK-Si.

Source: arXiv cs.RO | 2026-09-29