HCC: Small: A Physical Vocabulary for Human-Robot Interaction

HCC：小：人机交互的物理词汇

• 批准号: 1258213
• 负责人: William Smart
• 金额: $ 6.35万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1258213&HistoricalAwards=false
• 关键词: HCC; Small; Physical; Vocabulary; Human

We are the victims of our own success. We can now deploy mobile robots in real-world environments and have them operate completely autonomously for extended periods of time. We no longer have to surround our robots with graduate student wranglers to keep them functional, and to keep the general public at a safe distance. These technical successes mean that members of the general public must now interact directly with robots, without the aid of an interpreter. But members of the public are poorly equipped for such interactions, since they are unfamiliar with real robots and how they work. Thus, the interactions often go poorly; the robot is hindered in performing its task, and the human is unhappy. For people to be comfortable interacting with a robot, they must feel that they understand what it's thinking, what it's trying to do, and the actions that it will take. Moreover, people must be able to deduce this information from observing the robot for a short period of time, just as we do with other humans that we encounter. The fundamental problem here is that humans communicate a wealth of information by means of a non-verbal "vocabulary" in which body language (how we stand, how we hold our arms, etc.), eye contact, nods, and other subtle cues ostensibly not essential to the task at hand play significant roles. We do this naturally, and without conscious effort. Taken in context, this information allows us to infer another person's state of mind, goals, and intentions with surprising accuracy; this, in turn, allows us to predict how a given interaction will unfold, and gives us some control over it. Because people take this ability for granted, they suffer when it is absent, as is currently often the case when interacting with a mobile robot. The PI intends to address this deficiency in the current project. He argues that to make human-robot interactions as natural as possible, we must equip robots with our physical vocabulary and ensure that they use it appropriately, following social norms. To achieve this goal the PI will turn to the performing arts, where actors are trained to express themselves physically. A good actor can convey a vast amount of information about a character's state of mind, goals, and intentions by simply walking across the stage in a particular way. The actions may be styled, larger-than-life, or subtle, but they are intended to convey information about the character's internal mental state. The techniques that actors employ have been honed and refined for hundreds of years and tested for effectiveness on the general public. In this research, the PI will exploit such insights and skills to develop a physical vocabulary that can communicate beliefs, intentions, and goals to humans interacting with a robot, thereby enabling people to better predict the robot's actions. Finally, the PI will rigorously evaluate these actions to verify that they are actually useful. Broader Impacts: Robots are becoming more and more a part of our lives, and members of the public will be forced to deal with them sooner or later. If we have an understanding of the physical aspects of these interactions, the integration of robots into our everyday lives will be made much less painful and distressing.

我们是自己成功的受害者。我们现在可以在现实环境中部署移动机器人，让它们在很长一段时间内完全自主地运行。我们不再需要在机器人周围安排研究生来保持它们的功能，并与公众保持安全距离。这些技术上的成功意味着公众现在必须直接与机器人互动，而不需要口译员的帮助。但公众对这种互动知之甚少，因为他们不熟悉真正的机器人以及它们的工作原理。因此，互动往往很糟糕；机器人在执行任务时受到阻碍，而人类则不高兴。为了让人们能够舒适地与机器人互动，他们必须觉得自己理解机器人在想什么，它想要做什么，以及它将采取的行动。此外，人们必须能够从对机器人的短时间观察中推断出这些信息，就像我们对遇到的其他人所做的那样。这里的根本问题是，人类通过非语言的“词汇”来交流大量的信息，其中身体语言（我们如何站立，如何抱臂等），眼神交流，点头和其他表面上对手头任务无关紧要的微妙暗示发挥着重要作用。我们这样做是自然的，没有有意识的努力。在上下文中，这些信息使我们能够以惊人的准确性推断出另一个人的精神状态、目标和意图；反过来，这让我们能够预测一个给定的互动将如何展开，并给予我们一些控制。因为人们认为这种能力是理所当然的，所以当缺乏这种能力时，他们就会感到痛苦，就像目前与移动机器人互动时经常出现的情况一样。PI打算在当前项目中解决这一缺陷。他认为，为了使人机互动尽可能自然，我们必须为机器人配备我们的肢体词汇，并确保它们恰当地使用这些词汇，遵循社会规范。为了实现这一目标，PI将转向表演艺术，在表演艺术中，演员们接受训练来表达自己的身体。一个好的演员可以通过以一种特定的方式在舞台上行走来传达大量关于角色的心理状态、目标和意图的信息。这些动作可能是有风格的、夸张的或微妙的，但它们都是为了传达角色内心的心理状态。演员们使用的技巧经过数百年的磨练和完善，并在公众中测试了有效性。在这项研究中，PI将利用这些见解和技能来开发一种物理词汇，可以向与机器人互动的人类传达信念、意图和目标，从而使人们能够更好地预测机器人的行动。最后，PI将严格评估这些操作，以验证它们是否确实有用。更广泛的影响：机器人正越来越多地成为我们生活的一部分，公众迟早会被迫与它们打交道。如果我们对这些互动的物理方面有所了解，那么机器人融入我们的日常生活将会减少很多痛苦和困扰。