Meza-Pantoja A, Lawson A C, Caputo C C, Ge J, Cohen D J, Krieger A, Saeidi H
Department of Computer Science, University of North Carolina at Wilmington, Wilmington, NC 28403, USA.
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21211 USA.
IEEE Trans Med Robot Bionics. 2025 May;7(2):583-594. doi: 10.1109/tmrb.2025.3560400. Epub 2025 Apr 14.
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%.
机器人辅助手术(RAS)系统利用灵活的工具、增强的视觉和运动过滤功能来改善患者预后。虽然大多数RAS系统由外科医生直接控制,但由于其可重复性和精确性,自主RAS的开发和应用正在不断增加。尽管完全自主是一个长期目标,但在RAS中人为干预仍然至关重要。在这项工作中,我们开发并测试了一种用于机器人电外科手术的共享控制策略,其中自主机器人控制器和人类操作员相互协作。我们设计并实施了识别测试,评估自主控制策略和手动控制策略的有效性以及控制模式之间切换的成本。基于这些结果,我们提出了一种控制模式切换策略,并通过对猪舌样本进行精确切割的实验对其进行检验。结果表明,通过结合自主控制和手动控制的最佳要素,与单模式控制策略相比,我们可以实现更精确的软组织切口。此外,所提出的策略将所需的人工参与时间减少了69.29%。