A Review on the Form and Complexity of Human–Robot Interaction in the Evolution of Autonomous Surgery

IF 6.8 Q1 AUTOMATION & CONTROL SYSTEMS Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-07-09 DOI:10.1002/aisy.202400197
Tangyou Liu, Jiaole Wang, Shing Wong, Andrew Razjigaev, Susann Beier, Shuhua Peng, Thanh Nho Do, Shuang Song, Dewei Chu, Chun Hui Wang, Nigel H. Lovell, Liao Wu
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Abstract

As robotics and intelligence increasingly integrate into surgery, the pivotal role of human–robot interaction (HRI) in surgical procedures and outcomes becomes evident. However, debate rages over whether increasing robot autonomy will result in less human involvement. Some scholars assert that autonomy will reduce human participation, whereas others contend it will result in more complex interactions. To reveal the role of HRI in the evolution of autonomous surgery, this review systematically explores the HRI of robotic surgery with various levels of autonomy. The HRI is examined from both robotic science and clinical practice perspectives, incorporating relevant case studies. Two key components, intention detection and situation awareness, are especially concerned with a brief description of the interfaces and control strategies they rely on. Additional insights are drawn from analogous technologies in aviation, industrial robotics, and autonomous vehicles. The analysis suggests that HRI complexity tends to increase as the robot transitions from no autonomy to conditional autonomy and is predicted to subsequently decrease with a substantial shift in the interaction form when moving toward full autonomy. It is concluded by highlighting challenges from technical and clinical perspectives and delineating research trends in this rapidly evolving field.

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自主手术发展过程中人机互动的形式与复杂性综述
随着机器人技术和智能技术越来越多地融入外科手术,人机互动(HRI)在手术过程和结果中的关键作用变得显而易见。然而,关于机器人自主性的提高是否会导致人类参与减少的争论仍在激烈进行。一些学者认为,自主性会减少人类的参与,而另一些学者则认为,自主性会带来更复杂的互动。为了揭示人机交互在自主外科手术发展过程中的作用,本综述系统地探讨了具有不同自主水平的机器人外科手术的人机交互。本综述从机器人科学和临床实践两个角度,并结合相关案例研究,对人机交互界面进行了探讨。其中特别关注意图检测和情境感知这两个关键部分,并简要介绍了它们所依赖的界面和控制策略。此外,还从航空、工业机器人和自动驾驶汽车等领域的类似技术中汲取了更多启示。分析表明,当机器人从无自主过渡到有条件自主时,人机交互的复杂性往往会增加,而在向完全自主过渡时,随着交互形式的重大转变,复杂性预计会随之降低。最后,报告从技术和临床角度强调了所面临的挑战,并勾勒出这一快速发展领域的研究趋势。
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CiteScore
1.30
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0.00%
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0
审稿时长
4 weeks
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