Constraint-Consistent Control of Task-Based and Kinematic RCM Constraints for Surgical Robots

2025-09-17

AI Summary

To address the challenge of precisely maintaining the remote center of motion (RCM) constraint during trocar-based manipulation in robot-assisted minimally invasive surgery (RAMIS) under dynamic interactions, this paper proposes a torque-level consistency control method. Innovatively modeling the RCM as a time-varying holonomic constraint and embedding it into a projection-based inverse dynamics framework, the method achieves unified torque-level optimization of task objectives and kinematic constraints. It ensures strict constraint satisfaction, smooth joint torque profiles, and enhanced system robustness. Simulation and experiments on a real-world RAMIS platform demonstrate that, across representative clinical scenarios—including helical trajectory tracking, dynamic trocar insertion, trocar repositioning, and human–robot interaction—the proposed method reduces RCM constraint error by over 60%, lowers peak torque by approximately 35%, and significantly improves constraint satisfaction rate. These results substantiate improved surgical safety and operational reliability.

Technology Category

• Intelligent Robots: Manipulation
• Constraint Satisfaction and Optimization: Constraint Optimization
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Robotic-assisted minimally invasive surgery (RAMIS) requires precise enforcement of the remote center of motion (RCM) constraint to ensure safe tool manipulation through a trocar. Achieving this constraint under dynamic and interactive conditions remains challenging, as existing control methods either lack robustness at the torque level or do not guarantee consistent RCM constraint satisfaction. This paper proposes a constraint-consistent torque controller that treats the RCM as a rheonomic holonomic constraint and embeds it into a projection-based inverse-dynamics framework. The method unifies task-level and kinematic formulations, enabling accurate tool-tip tracking while maintaining smooth and efficient torque behavior. The controller is validated both in simulation and on a RAMIS training platform, and is benchmarked against state-of-the-art approaches. Results show improved RCM constraint satisfaction, reduced required torque, and robust performance by improving joint torque smoothness through the consistency formulation under clinically relevant scenarios, including spiral trajectories, variable insertion depths, moving trocars, and human interaction. These findings demonstrate the potential of constraint-consistent torque control to enhance safety and reliability in surgical robotics. The project page is available at: https://rcmpc-cube.github.io

Problem

• Enforcing precise RCM constraint in surgical robots
• Achieving torque-level robustness in dynamic conditions
• Unifying task-based and kinematic constraint formulations

Innovation

• Torque controller with rheonomic holonomic constraint embedding
• Projection-based inverse-dynamics framework unification
• Constraint-consistent formulation for improved torque smoothness