RCM Constraint-Consistent Dynamic Control in Surgical Robots
Yu Li, Hamid Sadeghian, Zewen Yang, Valentin Le Mesle, Sami Haddadin
AI summary
Problem
Existing virtual remote center of motion (RCM) controllers are typically formulated at the kinematic or task level, making consistent torque-level enforcement under trocar motion and physical interaction difficult.
Approach
The authors model the RCM as a rheonomic holonomic constraint and embed it into a projection-based inverse-dynamics controller that explicitly decomposes constrained and free-motion torques.
Key results
- Lower RCM residuals and smoother torque profiles in simulation and experiments
- Approximately half the total torque consumption compared to projection-Jacobian baselines
- Peak torques reduced by 77% relative to the Z-approach baseline
- Robust performance under varying insertion depths, moving trocar conditions, and human interaction
Why it matters
Enables safer, more reliable virtual RCM enforcement for robotic-assisted minimally invasive surgery under dynamic and interactive conditions.
Abstract
Robotic-assisted minimally invasive surgery (RAMIS) requires accurate enforcement of the remote center of motion (RCM) constraint to ensure safe tool motion through a trocar. Existing virtual RCM controllers are commonly formulated either at the kinematic level or as task-space objectives, which makes torque-level enforcement under trocar motion and physical interaction difficult to formulate consistently. This paper models the RCM as a rheonomic holonomic constraint and incorporates it into a projection-based inverse-dynamics controller with explicit constrained/free-motion torque decomposition. The resulting formulation unifies kinematic RCM enforcement and task-space tracking at the torque level, while preserving a constraint- consistent structure for residual regulation and null-space compliance. The proposed controller is validated in simulation and on a RAMIS training platform against representative projection-based and constrained-dynamics baselines. Across spiral tracking, varying insertion depth, moving trocar conditions, and human interaction, the method achieves lower RCM residuals and smoother torque profiles while maintaining accurate tool-tip tracking. These results support the use of constraint-consistent torque control for reliable virtual RCM enforcement in surgical robotics. The project page is available at https://rcmpc-cube.github.io.