Physical interaction between humans and robots can help robots learn to perform complex tasks. The robot arm gains information by observing how the human kinesthetically guides it throughout the task. While prior works focus on how the robot learns, it is equally important that this learning is transparent to the human teacher. Visual displays that show the robot's uncertainty can potentially communicate this information; however, we hypothesize that visual feedback mechanisms miss out on the physical connection between the human and robot. In this work we present a soft haptic display that wraps around and conforms to the surface of a robot arm, adding a haptic signal at an existing point of contact without significantly affecting the interaction. We demonstrate how soft actuation creates a salient haptic signal while still allowing flexibility in device mounting. Using a psychophysics experiment, we show that users can accurately distinguish inflation levels of the wrapped display with an average Weber fraction of 11.4%. When we place the wrapped display around the arm of a robotic manipulator, users are able to interpret and leverage the haptic signal in sample robot learning tasks, improving identification of areas where the robot needs more training and enabling the user to provide better demonstrations. See videos of our device and user studies here: https://youtu.be/tX-2Tqeb9Nw
翻译:人类和机器人之间的物理互动可以帮助机器人学会执行复杂的任务。 机器人手臂通过观察人类运动在任务中如何引导它获得信息。 虽然先前的工作侧重于机器人如何学习, 但同样重要的是, 学习对教师来说是透明的。 显示机器人不确定性的视觉显示可以传递这些信息; 但是, 我们假设视觉反馈机制会错开人类和机器人之间的物理联系。 在这项工作中, 我们展示一个软机智显示, 环绕机器人手臂的表面, 并符合机器人手臂的表面, 在现有的接触点添加一个偶然信号, 而不会显著影响互动。 我们演示软动作如何产生突出的随机信号, 同时仍然允许设备安装的灵活性。 使用心理物理实验, 我们显示用户可以准确地区分包装显示的通胀水平, 平均为 11. 4% 的 Weber 部分。 当我们把包装的显示放在机器人操纵器的臂上时, 用户能够解释并利用机械臂的表面信号, 在抽样学习任务中, 改进对机器人需要更多培训的领域的识别, 并且使用户能够提供更好的演示。 见 MAS-2 。