A Concurrent Framework for Constrained Inverse Kinematics of Minimally Invasive Surgical Robots

Endoscope Automation Framework with Hierarchical Control and Interactive Perception for Multi-Tool Tracking in Minimally Invasive Surgery

In the context of Minimally Invasive Surgery, surgeons mainly rely on visual feedback during medical operations. In common procedures such as tissue resection, the automation of endoscopic control is crucial yet challenging, particularly due to the interactive dynamics of multi-agent operations and the necessity for real-time adaptation. This paper introduces a novel framework that unites a Hierarchical Quadratic Programming controller with an advanced interactive perception module. This integration addresses the need for adaptive visual field control and robust tool tracking in the operating scene, ensuring that surgeons and assistants have optimal viewpoint throughout the surgical task. The proposed framework handles multiple objectives within predefined thresholds, ensuring efficient tracking even amidst changes in operating backgrounds, varying lighting conditions, and partial occlusions. Empirical validations in scenarios involving single, double, and quadruple tool tracking during tissue resection tasks have underscored the system's robustness and adaptability. The positive feedback from user studies, coupled with the low cognitive and physical strain reported by surgeons and assistants, highlight the system's potential for real-world application.

Implementation of a Virtual Reality Based Digital-Twin Robotic Minimally Invasive Surgery Simulator

The rapid development of computers and robots has seen robotic minimally invasive surgery (RMIS) gradually enter the public's vision. RMIS can effectively eliminate the hand vibrations of surgeons and further reduce wounds and bleeding. However, suitable RMIS and virtual reality-based digital-twin surgery trainers are still in the early stages of development. Extensive training is required for surgeons to adapt to different operating modes compared to traditional MIS. A virtual-reality-based digital-twin robotic minimally invasive surgery (VRDT-RMIS) simulator was developed in this study, and its effectiveness was introduced. Twenty-five volunteers were divided into two groups for the experiment, the Expert Group and the Novice Group. The use of the VRDT-RMIS simulator for face, content, and structural validation training, including the peg transfer module and the soft tissue cutting module, was evaluated. Through subjective and objective evaluations, the potential roles of vision and haptics in robot surgery training were explored. The simulator can effectively distinguish surgical skill proficiency between experts and novices.

Dimensional optimisation and an inverse kinematic solution method of a safety-enhanced remote centre of motion manipulator

BACKGROUND

With the expansion of minimally invasive surgery (MIS) applications in surgery, the remote centre of motion (RCM) manipulator requires a more flexible workspace to meet different operation requirements. Thus, the mechanical structure and motion control of the RCM manipulator play important roles.

METHODS

A multi-objective genetic algorithm was exploited to maximise the kinematic performance and obtain a compact structure of the RCM manipulator. An inverse kinematic solution method is proposed to meet task accuracy and kinematic singularity avoidance constraints for safety motion control.

RESULTS

Simulation results demonstrate that there are significant improvements in the reachable workspace inside the abdominal cavity, the flexibility of the workspace, kinematic performance, and compactness of the RCM manipulator. Experiments verify the feasibility of the prototype and the validity of the proposed inverse kinematic solution method.

CONCLUSIONS

This enhances the adaptability and safety of the RCM manipulator and provides potential prospects for MIS application.