Alvarez Valdivia Antonio, Habibian Soheil, Mendenhall Carly A, Fuentes Francesco, Shailly Ritish, Losey Dylan P, Blumenschein Laura H
IEEE Trans Haptics. 2023 Jan-Mar;16(1):57-72. doi: 10.1109/TOH.2023.3240400. Epub 2023 Mar 21.
Humans can leverage physical interaction to teach robot arms. As the human kinesthetically guides the robot through demonstrations, the robot learns the desired task. While prior works focus on how the robot learns, it is equally important for the human teacher to understand what their robot is learning. Visual displays can communicate this information; however, we hypothesize that visual feedback alone misses out on the physical connection between the human and robot. In this paper we introduce a novel class of soft haptic displays that wrap around the robot arm, adding signals without affecting that interaction. We first design a pneumatic actuation array that remains flexible in mounting. We then develop single and multi-dimensional versions of this wrapped haptic display, and explore human perception of the rendered signals during psychophysic tests and robot learning. We ultimately find that people accurately distinguish single-dimensional feedback with a Weber fraction of 11.4%, and identify multi-dimensional feedback with 94.5% accuracy. When physically teaching robot arms, humans leverage the single- and multi-dimensional feedback to provide better demonstrations than with visual feedback: our wrapped haptic display decreases teaching time while increasing demonstration quality. This improvement depends on the location and distribution of the wrapped haptic display.
人类可以利用身体互动来训练机器人手臂。当人类通过示范对机器人进行动觉引导时，机器人就能学会所需完成的任务。虽然先前的研究工作聚焦于机器人如何学习，但对于人类教师而言，了解他们的机器人正在学习什么同样重要。视觉显示器可以传达此类信息；然而，我们推测仅靠视觉反馈会忽略人与机器人之间的身体联系。在本文中，我们引入了一种新型的柔软触觉显示器，它环绕在机器人手臂周围，在不影响互动的情况下添加信号。我们首先设计了一种在安装时仍保持灵活的气动驱动阵列。然后，我们开发了这种环绕式触觉显示器的单维和多维版本，并在心理物理学测试和机器人学习过程中探索人类对所呈现信号的感知。我们最终发现，人们能够以11.4%的韦伯分数准确区分一维反馈，并以94.5%的准确率识别多维反馈。在对机器人手臂进行实际训练时，人类利用单维和多维反馈，相较于视觉反馈能提供更好的示范：我们的环绕式触觉显示器减少了教学时间，同时提高了示范质量。这种改进取决于环绕式触觉显示器的位置和分布。
