Humans Need Augmented Feedback to Physically Track Non-Biological Robot Movements
Humans Need Augmented Feedback to Physically Track Non-Biological Robot Movements
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DOI：
10.1109/icra48891.2023.10161075
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Mahdiar Edraki;P. Maurice;D. Sternad
中科院分区：
文献类型：
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作者：
Mahdiar Edraki;P. Maurice;D. Sternad
人类与机器人有效协作的一个重要组成部分是它们的运动的兼容性，特别是当人类与机器人合作时。根据先前的研究结果，人类与以类似人类或生物速度轮廓移动的机器人进行更无缝的互动，这项研究研究探讨了人类是否能够适应违反人类特征的机器人。具体的重点是广泛的实践和实时增强反馈的作用。六组参与者物理跟踪一个机器人跟踪一个椭圆形的配置文件，其中速度缩放的曲率的路径在生物和非生物的方式，同时指示，以尽量减少与机器人的相互作用力。6组中的3组接受了关于其力误差的实时视觉反馈。结果表明，在每天3次的练习中，当机器人的轨迹违反人类的速度模式时，当给出关于其力误差的反馈时，人类可以减少其相互作用力。相反，当不提供增强反馈时，尽管进行了广泛的实践，但没有改善。即使有反馈，生物特征也没有显示出改善，表明（非零）力已经达到最低水平。这些发现强调了生物机器人轨迹和增强反馈的重要性，以指导人类适应物理人机交互中的非生物运动。这些结果对机器人技术的各个领域都有影响，例如外科手术应用和工业协作机器人。
An important component for the effective collaboration of humans with robots is the compatibility of their movements, especially when humans physically collaborate with a robot partner. Following previous findings that humans interact more seamlessly with a robot that moves with human-like or biological velocity profiles, this study examined whether humans can adapt to a robot that violates human signatures. The specific focus was on the role of extensive practice and real-time augmented feedback. Six groups of participants physically tracked a robot tracing an ellipse with profiles where velocity scaled with the curvature of the path in biological and non-biological ways, while instructed to minimize the interaction force with the robot. Three of the 6 groups received real-time visual feedback about their force error. Results showed that with 3 daily practice sessions, when given feedback about their force errors, humans could decrease their interaction forces when the robot's trajectory violated human-like velocity patterns. Conversely, when augmented feedback was not provided, there were no improvements despite this extensive practice. The biological profile showed no improvements, even with feedback, indicating that the (non-zero) force had already reached a floor level. These findings highlight the importance of biological robot trajectories and augmented feedback to guide humans to adapt to non-biological movements in physical human-robot interaction. These results have implications on various fields of robotics, such as surgical applications and collaborative robots for industry.