Hamlyn Centre for Robotic Surgery, Imperial College London, UK.
Ann Biomed Eng. 2012 Oct;40(10):2156-67. doi: 10.1007/s10439-012-0578-4. Epub 2012 May 12.
The use of multiple robots for performing complex tasks is becoming a common practice for many robot applications. When different operators are involved, effective cooperation with anticipated manoeuvres is important for seamless, synergistic control of all the end-effectors. In this paper, the concept of Collaborative Gaze Channelling (CGC) is presented for improved control of surgical robots for a shared task. Through eye tracking, the fixations of each operator are monitored and presented in a shared surgical workspace. CGC permits remote or physically separated collaborators to share their intention by visualising the eye gaze of their counterparts, and thus recovers, to a certain extent, the information of mutual intent that we rely upon in a vis-à-vis working setting. In this study, the efficiency of surgical manipulation with and without CGC for controlling a pair of bimanual surgical robots is evaluated by analysing the level of coordination of two independent operators. Fitts' law is used to compare the quality of movement with or without CGC. A total of 40 subjects have been recruited for this study and the results show that the proposed CGC framework exhibits significant improvement (p < 0.05) on all the motion indices used for quality assessment. This study demonstrates that visual guidance is an implicit yet effective way of communication during collaborative tasks for robotic surgery. Detailed experimental validation results demonstrate the potential clinical value of the proposed CGC framework.
使用多个机器人来执行复杂任务对于许多机器人应用来说已经成为一种常见做法。当涉及到不同的操作人员时,对于所有末端执行器的无缝、协同控制,与预期动作进行有效的协作是很重要的。本文提出了协作凝视引导(CGC)的概念,以改进用于共享任务的手术机器人的控制。通过眼动追踪,监控每个操作人员的注视点,并在共享的手术工作空间中呈现出来。CGC 允许远程或物理分离的协作者通过可视化其对应方的眼注视来共享他们的意图,从而在一定程度上恢复了我们在面对面工作环境中依赖的相互意图信息。在这项研究中,通过分析两个独立操作人员的协调程度,评估了使用和不使用 CGC 控制一对双手手术机器人进行手术操作的效率。使用 Fitts 定律来比较有和没有 CGC 的运动质量。这项研究共招募了 40 名受试者,结果表明,所提出的 CGC 框架在用于质量评估的所有运动指标上都表现出显著的改善(p<0.05)。这项研究表明,视觉引导是机器人手术协作任务中一种隐含但有效的沟通方式。详细的实验验证结果证明了所提出的 CGC 框架的潜在临床价值。