A Confidence-Based Shared Control Strategy for Robotic Electrosurgery

Abstract

Robotic-assisted surgery (RAS) systems take advantage of dexterous tools, enhanced vision, and motion filtering to improve patient outcomes. Whereas most RAS systems are directly controlled by surgeons, the development and application of autonomous RAS are growing owing to their repeatability and precision. Although full autonomy is a long-term goal, human intervention in RAS is still essential. In this work, we develop and test a shared control strategy for robotic electrosurgery in which autonomous robot controllers and human operators collaborate. We designed and implemented identification tests that assessed the effectiveness of autonomous and manual control strategies and the cost of switching between the control modes. Based on the results, we propose a control mode switching strategy and examine it via an experiment on precision cutting on porcine tongue samples. The results indicate that by combining the best elements of autonomous and manual control, we can achieve more accurate soft-tissue incisions as compared to single-mode control strategies. Furthermore, the proposed strategy reduces the required human-in-the-loop time by 69.29%.