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A Confidence-Based Shared Control Strategy for the Smart Tissue Autonomous Robot (STAR)

机译:智能组织自治机器人(STAR)的基于信心的共享控制策略

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摘要

Autonomous robotic assisted surgery (RAS) systems aim to reduce human errors and improve patient outcomes leveraging robotic accuracy and repeatability during surgical procedures. However, full automation of RAS in complex surgical environments is still not feasible and collaboration with the surgeon is required for safe and effective use. In this work, we utilize our Smart Tissue Autonomous Robot (STAR) to develop and evaluate a shared control strategy for the collaboration of the robot with a human operator in surgical scenarios. We consider 2D pattern cutting tasks with partial blood occlusion of the cutting pattern using a robotic electrocautery tool. For this surgical task and RAS system, we i) develop a confidence-based shared control strategy, ii) assess the pattern tracking performances of manual and autonomous controls and identify the confidence models for human and robot as well as a confidence-based control allocation function, and iii) experimentally evaluate the accuracy of our proposed shared control strategy. In our experiments on porcine fat samples, by combining the best elements of autonomous robot controller with complementary skills of a human operator, our proposed control strategy improved the cutting accuracy by 6.4%, while reducing the operator work time to 44 % compared to a pure manual control.
机译:自主机器人辅助手术(RAS)系统旨在减少人为错误并在手术过程中利用机器人的准确性和可重复性来改善患者的预后。但是,在复杂的手术环境中实现RAS的完全自动化仍然不可行,并且需要与外科医生合作才能安全有效地使用。在这项工作中,我们利用我们的智能组织自主机器人(STAR)来开发和评估一种共享控制策略,用于在手术场景中该机器人与人类操作员的协作。我们考虑使用机器人电灼工具将2D模式切割任务与部分切割模式的血液阻塞在一起。对于此外科手术任务和RAS系统,我们i)开发基于信任的共享控制策略,ii)评估手动和自主控制的模式跟踪性能,并确定人和机器人的信任模型以及基于信任的控制分配功能;以及iii)实验评估我们提出的共享控制策略的准确性。在我们对猪脂肪样品的实验中,通过将自动机器人控制器的最佳元素与人类操作员的互补技能相结合,我们提出的控制策略将切割精度提高了6.4%,而与单纯操作相比,操作员的工作时间减少到44%手动。

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