Admittance Control for Adaptive Remote Center of Motion in Robotic Laparoscopic Surgery

TL;DR

The paper addresses the challenge of preserving a fixed remote center of motion (RCM) in robotic laparoscopic surgery when external body motions shift the trocar. It introduces a framework that couples admittance control with a redundancy-resolution-based kinematic model, using force/torque feedback at the instrument base to estimate RCM forces. The main contributions are an augmented Jacobian formulation for RCM and instrument constraints, a robust force-estimation method to decouple RCM and distal forces, and comprehensive simulations in MATLAB and ROS2 on multiple 7-DoF platforms, plus a hardware prototype. This approach enables more compliant, force-aware RCM tracking without relying on external markers, facilitating future experimental validation in a realistic MIS setting.

Abstract

In laparoscopic robot-assisted minimally invasive surgery, the kinematic control of the robot is subject to the remote center of motion (RCM) constraint at the port of entry (e.g., trocar) into the patient's body. During surgery, after the instrument is inserted through the trocar, intrinsic physiological movements such as the patient's heartbeat, breathing process, and/or other purposeful body repositioning may deviate the position of the port of entry. This can cause a conflict between the registered RCM and the moved port of entry. To mitigate this conflict, we seek to utilize the interaction forces at the RCM. We develop a novel framework that integrates admittance control into a redundancy resolution method for the RCM kinematic constraint. Using the force/torque sensory feedback at the base of the instrument driving mechanism (IDM), the proposed framework estimates the forces at RCM, rejects forces applied on other locations along the instrument, and uses them in the admittance controller. In this paper, we report analysis from kinematic simulations to validate the proposed framework. In addition, a hardware platform has been completed, and future work is planned for experimental validation.

Figures (6)

• Figure 1: The developed hardware platform includes a 7-DoF robot, a customized IDM, an ATI Gamma F/T sensor, and a surgical instrument.
• Figure 2: Schematic representation of RCM on a surgical robot's end-effector subject to external forces.
• Figure 3: The stiffness-damping behavior of a 1-DoF model for the end-effector at the RCM point during operation.
• Figure 4: Simulation plots include: 1) Convergence of the force acting upon the RCM point from the patient’s body with the proposed control algorithm. 2) Convergence of the estimated criterion metric, $\hat{\gamma}$, with the applied force loads. 3) Convergence of position and velocity errors with the exerted force acting upon the RCM point.
• Figure 5: Trocar-RCM linear displacement simulation: 1) A surgical room featuring a 7-DoF robot virtual model, representing the shoulder (3 DoF), elbow (1 DoF), and wrist (3 DoF), subject to the patient's body motion, causing a 2cm linear path trajectory of the Trocar-RCM. 2) The exerted force converges to zero with the proposed admittance controller.