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评估注视跟踪在利用多模态反馈优化人在回路中的远程机器人操作中的作用。

Assessing the Role of Gaze Tracking in Optimizing Humans-In-The-Loop Telerobotic Operation Using Multimodal Feedback.

作者信息

Bolarinwa Joseph, Eimontaite Iveta, Mitchell Tom, Dogramadzi Sanja, Caleb-Solly Praminda

机构信息

Bristol Robotics Laboratory, University of the West of England (UWE), Bristol, United Kingdom.

Creative Technologies Lab, University of the West of England (UWE), Bristol, United Kingdom.

出版信息

Front Robot AI. 2021 Oct 4;8:578596. doi: 10.3389/frobt.2021.578596. eCollection 2021.

Abstract

A key challenge in achieving effective robot teleoperation is minimizing teleoperators' cognitive workload and fatigue. We set out to investigate the extent to which gaze tracking data can reveal how teleoperators interact with a system. In this study, we present an analysis of gaze tracking, captured as participants completed a multi-stage task: grasping and emptying the contents of a jar into a container. The task was repeated with different combinations of visual, haptic, and verbal feedback. Our aim was to determine if teleoperation workload can be inferred by combining the gaze duration, fixation count, task completion time, and complexity of robot motion (measured as the sum of robot joint steps) at different stages of the task. Visual information of the robot workspace was captured using four cameras, positioned to capture the robot workspace from different angles. These camera views (aerial, right, eye-level, and left) were displayed through four quadrants (top-left, top-right, bottom-left, and bottom-right quadrants) of participants' video feedback computer screen, respectively. We found that the gaze duration and the fixation count were highly dependent on the stage of the task and the feedback scenario utilized. The results revealed that combining feedback modalities reduced the cognitive workload (inferred by investigating the correlation between gaze duration, fixation count, task completion time, success or failure of task completion, and robot gripper trajectories), particularly in the task stages that require more precision. There was a significant positive correlation between gaze duration and complexity of robot joint movements. Participants' gaze outside the areas of interest (distractions) was not influenced by feedback scenarios. A learning effect was observed in the use of the controller for all participants as they repeated the task with different feedback combination scenarios. To design a system for teleoperation, applicable in healthcare, we found that the analysis of teleoperators' gaze can help understand how teleoperators interact with the system, hence making it possible to develop the system from the teleoperators' stand point.

摘要

实现有效的机器人远程操作的一个关键挑战是尽量减少远程操作员的认知工作量和疲劳。我们着手研究注视跟踪数据能够在多大程度上揭示远程操作员与系统的交互方式。在本研究中,我们对注视跟踪进行了分析,这些数据是在参与者完成一项多阶段任务时捕获的:抓取罐子里的物品并将其倒入容器中。该任务在不同的视觉、触觉和言语反馈组合下重复进行。我们的目的是确定是否可以通过结合任务不同阶段的注视持续时间、注视次数、任务完成时间和机器人运动复杂度(以机器人关节步数总和衡量)来推断远程操作工作量。使用四个摄像头捕获机器人工作空间的视觉信息,这些摄像头的位置能够从不同角度捕捉机器人工作空间。这些摄像头视图(俯视、右侧、平视和左侧)分别通过参与者视频反馈电脑屏幕的四个象限(左上、右上、左下和右下象限)显示。我们发现注视持续时间和注视次数高度依赖于任务阶段以及所使用的反馈场景。结果表明,结合反馈模式可减少认知工作量(通过研究注视持续时间、注视次数、任务完成时间、任务完成的成功或失败以及机器人夹爪轨迹之间的相关性推断得出),尤其是在需要更高精度的任务阶段。注视持续时间与机器人关节运动复杂度之间存在显著的正相关。参与者在感兴趣区域之外(分心区域)的注视不受反馈场景的影响。当所有参与者在不同反馈组合场景下重复任务时,观察到他们在使用控制器方面存在学习效应。为了设计一个适用于医疗保健领域的远程操作系统,我们发现对远程操作员注视的分析有助于理解他们与系统的交互方式,从而有可能从远程操作员的角度开发该系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d2a/8521448/f13f41ff2cab/frobt-08-578596-g001.jpg

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