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 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. You can see videos of our device and experiments here: https://youtu.be/yPcMGeqsjdM
翻译:人类可以利用物理互动来教授机器人的臂膀。 当人类运动学通过演示来引导机器人时, 机器人会学习理想的任务。 虽然先前的工作侧重于机器人的学习方式, 但人类老师理解机器人的学习方式是同样重要的。 视觉显示可以传达这些信息; 但是, 我们假设视觉反馈仅仅在人类和机器人之间的物理联系上就忽略了视觉反馈。 在本文中, 我们引入了一个新的软性机能显示类别, 环绕机器人手臂, 添加信号而不影响互动 。 我们首先设计一个气动感应阵列, 仍然灵活地安装。 然后我们开发这个包装机能显示的单一和多维的版本, 并探索人类在心理物理测试和机器人学习期间对所发出信号的感知。 我们最终发现人们能够准确地区分单维伯部分11.4%的单维特反馈, 并找出精确度为94.5%的多维的反馈。 当实际教授机器人武器时, 人类会利用单维和多维的反馈来提供更好的演示, 比视觉反馈更好: 我们包装的自动显示显示减少教学时间, 同时提高演示质量。 这种改进了我们包装的显示过程。 这种改进取决于这里的实验和MG/ 的显示方式, 您可以 显示地点的定位和显示位置和图像的分布。 显示。 显示: 这里的定位/ 显示。