论文标题
包裹触觉显示在机器人臂上以交流学习
Wrapping Haptic Displays Around Robot Arms to Communicate Learning
论文作者
论文摘要
人类可以利用身体互动来教机器人武器。当人类的动力学通过示范引导机器人时,机器人学习了所需的任务。尽管先前的工作重点是机器人学习方式,但对于人类老师来说,了解其机器人正在学习的内容同样重要。视觉显示可以传达此信息;但是,我们假设仅视觉反馈就错过了人与机器人之间的物理联系。在本文中,我们介绍了一类新颖的软性触觉显示器,这些显示器包裹在机器人的臂上,添加信号而不会影响这种相互作用。我们首先设计一个气动驱动阵列,该阵列在安装方面保持灵活。然后,我们开发了这种包裹的触觉显示的单一和多维版本,并在心理物理测试和机器人学习过程中探索了人类对渲染信号的看法。我们最终发现,人们以11.4%的韦伯(Weber)分数准确区分单维反馈,并以94.5%的精度确定多维反馈。当物理教授机器人臂时,人类利用单维反馈来提供比视觉反馈更好的演示:我们包装的触觉显示会降低教学时间,同时提高演示质量。这种改进取决于包裹的触觉显示的位置和分布。您可以在此处查看我们的设备和实验的视频:https://youtu.be/ypcmgeqsjdm
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. You can see videos of our device and experiments here: https://youtu.be/yPcMGeqsjdM