Extended Reality Check: Evaluating XR Prototyping for Human-Robot Interaction in Contact-Intensive Tasks.

IF 6.5
Tonia Mielke, Mareen Allgaier, Christian Hansen, Florian Heinrich
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Abstract

Extended Reality (XR) has the potential to improve efficiency and safety in the user-centered development of human-robot interaction. However, the validity of using XR prototyping for user studies for contact-intensive robotic tasks remains underexplored. These in-contact tasks are particularly relevant due to challenges arising from indirect force perception in robot control. Therefore, in this work, we investigate a representative example of such a task: robotic ultrasound. A user study was conducted to assess the transferability of results from a simulated user study to real-world conditions, comparing two force-assistance approaches. The XR simulation replicates the physical study set-up employing a virtual robotic arm, its control interface, ultrasound imaging, and two force-assistance methods: automation and force visualization. Our results indicate that while differences in force deviation, perceived workload, and trust emerge between real and simulated setups, the overall findings remain consistent. Specifically, partial automation of robot control improves performance and trust while reducing workload, and visual feedback decreases force deviation in both real and simulated conditions. These findings highlight the potential of XR for comparative studies, even in complex robotic tasks.

扩展现实检验:在接触密集型任务中评估人机交互的XR原型。
扩展现实(XR)在以用户为中心的人机交互开发中具有提高效率和安全性的潜力。然而,在接触密集型机器人任务的用户研究中使用XR原型的有效性仍未得到充分探索。由于机器人控制中间接力感知的挑战,这些接触任务特别相关。因此,在这项工作中,我们研究了这样一个任务的代表性例子:机器人超声。进行了一项用户研究,以评估模拟用户研究结果到现实世界条件的可转移性,比较了两种力辅助方法。XR仿真采用虚拟机械臂、其控制界面、超声成像和两种力辅助方法(自动化和力可视化)复制了物理研究设置。我们的研究结果表明,虽然在真实和模拟设置之间存在力偏差、感知工作量和信任方面的差异,但总体发现是一致的。具体来说,机器人控制的部分自动化在减少工作量的同时提高了性能和信任度,视觉反馈减少了真实和模拟条件下的力偏差。这些发现突出了XR在比较研究中的潜力,即使是在复杂的机器人任务中。
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