Collaborative Research: HCC: Small: Leveraging a Wrapped Haptic Display to Communicate Robot Learning and Accelerate Human Teaching

合作研究：HCC：小型：利用包裹式触觉显示器来传达机器人学习并加速人类教学

• 批准号: 2129201
• 负责人: Dylan Losey
• 金额: $ 24.97万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2129201&HistoricalAwards=false
• 关键词: Collaborative; Research; HCC; Small; Leveraging

Humans excel at teaching physical activities and tasks through demonstration and physical correction (think of a coach guiding an athlete through a desired motion), and human learners often use verbal and nonverbal signals to communicate their understanding or confusion. Similar approaches to teaching have been used between humans and robots, allowing humans to naturally demonstrate tasks, like cooking or furniture assembly, and correct errors in the motions of the robots. While robots have made great advances in understanding the demonstrations and corrections from human teachers, they have lacked an effective way to communicate what they do and do not understand, so human teachers may not know when or if a robot is ready to carry out a task by itself. This project will address this communication gap by developing new ways for robot arms to communicate to human teachers as they learn. The investigators will attach haptic skin displays (arrays of controllable bubbles) to a robotic arm and create touch sensations to communicate the robot’s understanding or confusion to the human teacher. Better and more understandable communication from robots as they learn will allow users to train or retrain robots more efficiently, and to better know when they are ready to deploy, without needing specialized knowledge about how robots function. These features will make robot arms more attractive tools for small and mid-sized manufacturers, allowing them to flexibly automate some manufacturing tasks. The lessons learned about communicating the learning state of robotic arms can also be applied to other computer and robotic systems, making the opaque process of robot and computer learning more comprehensible and giving the opportunity to catch and correct errors.The goal of this project is to characterize how humans perceive haptic skin displays wrapped around robot arms, and to formalize how robots capture and communicate feedback through these haptic arrays. Prior work enables robots to learn from physical demonstrations; however, it is equally important to make this learning transparent to the human teacher. This project will advance transparent and interpretable robot learning from an algorithmic and haptic perspective. The team of investigators will i) characterize the types and patterns of exploratory haptic feedback the human perceives, ii) embed the robot's complex and high-dimensional reward learning into low-dimensional haptic feedback, and iii) model how humans interpret the robot's feedback. These steps will ultimately provide human teachers with an awareness of the robot’s understanding and thereby improve their demonstrations. Each contribution will be evaluated in human subject studies with a commercial robot arm. This project has the potential to advance robotics in small and mid-sized manufacturing by making the process of teaching robot arms intuitive, transparent, and user-friendly.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

人类擅长通过演示和身体矫正来教授体育活动和任务（想象一下教练指导运动员完成所需的动作），并且人类学习者经常使用言语和非言语信号来传达他们的理解或困惑。虽然机器人在理解人类老师的演示和纠正方面取得了巨大进步，但它们缺乏有效的方法。传达他们所做的事情和所做的事情不理解，因此人类教师可能不知道机器人何时或是否准备好自行执行任务，该项目将通过开发机器人手臂在学习时与人类教师进行交流的新方法来解决这一沟通差距。将触觉皮肤显示器（可控气泡阵列）连接到机械臂上，并产生触觉，以将机器人的理解或困惑传达给人类老师。机器人在学习时更好、更容易理解的交流将使用户能够更有效地训练或再训练机器人。 ，并为了更好知道他们何时准备好部署，而无需了解机器人如何运作的专业知识，这些功能将使机器人手臂成为对中小型制造商更有吸引力的工具，使他们能够灵活地自动化一些制造任务。机械臂的状态也可以应用于其他计算机和机器人系统，使机器人和计算机学习的不透明过程更加容易理解，并提供捕捉和纠正错误的机会。该项目的目标是描述人类如何感知触觉皮肤显示缠绕在机器人手臂上，并正式确定机器人如何通过这些触觉阵列捕获和传达反馈；然而，使这种学习对人类教师透明也同样重要，该项目将推进透明且可解释的机器人学习。研究人员团队将i）描述人类感知的探索性触觉反馈的类型和模式，ii）将机器人复杂且高维的奖励学习嵌入到低维触觉中。反馈，以及 iii）模拟人类如何解释机器人的反馈。这些步骤最终将使人类教师了解机器人的理解，从而改进他们的演示，并在该项目中使用商业机器人手臂进行评估。通过使机器人手臂的示教过程体现直观、透明和用户友好，有潜力推进中小型制造业的机器人技术。该奖项是 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持和更广泛的影响审查标准。

项目成果

Wrapped Haptic Display for Communicating Physical Robot Learning

用于交流物理机器人学习的包裹式触觉显示器

• DOI: 10.1109/robosoft54090.2022.9762210
• 发表时间: 2022-04
• 期刊: 2022 IEEE 5th International Conference on Soft Robotics (RoboSoft
• 作者: Valdivia, Antonio Alvarez;Shailly, Ritish;Seth, Naman;Fuentes, Francesco;Losey, Dylan P.;Blumenschein, Laura H.
• 通讯作者: Blumenschein, Laura H.