Developing Technologies for Regulating Robot Persuasion in Human-Robot Interaction

机器人正在成为个人护理、教育和搜救等领域的可行工具，在这些领域，它们越来越多地作为自主或半自主的工具和助手与人一起工作。除了困难的机器人工程挑战外，进入人类空间的机器人还必须拥有有效的接口技术，支持人与机器人的交互，并使普通公众-不仅是机器人专家-能够与机器人合作，发出命令，并从它们那里获取数据。 与人类并列的机器人使用类似人类的社交技术，如手势或凝视，利用人类现有的人际交往技能来简化交互。这些社交机器人通常会向人们提供建议，研究表明，专家参考机器人如何比预期更有说服力，部分原因是人们对机器人的记忆、知识和计算能力的信任。这可能是危险的，例如，当医疗保健提供者与专业医疗机器人相矛盾时，可能会怀疑他们的评估，但也可能是可取的，例如，一个有说服力的康复机器人可以帮助进行康复练习。研究已经证实，机器人可以具有说服力，但人们对如何实际创造一个机器人来与人互动以避免或鼓励说服力知之甚少。短期内，我建议开发第一个互动框架和技术，展示机器人如何通过改变它们与人互动的方式来改变它们的说服力，特别是针对机器人如何使用其肢体语言。从长远来看，我的计划将帮助建立一个坚实的理解和一系列工具，为机器人编程，以便有效和适当地与人互动。 我的项目将从方法论上研究机器人如何使用他们的身体来影响说服；具体地说，机器人如何使用他们的手势、姿势、凝视和人际空间的使用来增加或减少说服力。我将实施并正式评估使机器人能够利用这些技术进行交互的原始接口技术和算法。为此，我将建立第一个用于测量和比较机器人设计说服力的方法学和度量标准，并进行一系列实验，以开发工程机器人说服的界面设计框架。 这项工作将为理解细微差别的机器人行为如何影响说服提供基础，包括面向说服的界面指南，以及一些用于构建机器人说服的首批交互技术和算法。归根结底，这对于使人-机器人交互程序员能够控制他们的机器人将是重要的：在潜在危险的情况下降低机器人的说服力，或者在适当的时候让机器人更有说服力。

Robots are emerging as viable tools in domains including personal care, education, and search and rescue, where they increasingly work alongside people as autonomous or semi-autonomous tools and assistants. In addition to the difficult robotics engineering challenges, robots that enter people's spaces must also have effective interface technologies that support human-robot interaction and enable the general public - not only robotics experts - to work with robots, give commands, and to get data from them. Robots collocated with people use human-like social techniques such as gestures or gaze, leveraging people's existing inter-personal skills to simplify interaction. These social robots will often be in positions where they offer recommendations to people, and research has shown how expert-reference robots can be more persuasive than anticipated, in part due to people's trust in robotic memory, knowledge, and computational ability. This can be dangerous, for example a healthcare provider may doubt their assessment when contradicted by a specialized healthcare robot, but can also be desirable, for example a persuasive rehabilitation robot could help with recovery exercises. Research has established that robots can be persuasive, but little is known about how to practically create a robot to interact with people to either avoid or encourage persuasion. In the short term, I propose to develop the first interaction framework and technologies that demonstrate how robots can modify their persuasiveness by changing how they interact with people, specifically targeting how a robot can use its body language. In the long term, my program will help build a solid understanding and array of tools for programming robots to interact effectively and appropriately with people. My program will methodologically investigate how robots can use their physical body to impact persuasion; specifically, how robots can use their gestures, posture, gaze, and use of interpersonal space, to increase or decrease persuasiveness. I will implement and formally evaluate original interface technologies and algorithms for enabling robots to leverage these techniques for interaction. For this I will establish the first methodologies and metrics for measuring and comparing persuasiveness of robotic designs, and conduct a series of experiments to develop interface design frameworks for engineering robot persuasion. This work will provide foundations for understanding how nuanced robotic behaviors can impact persuasion, including persuasion-oriented interface guidelines, and some of the first interaction techniques and algorithms for architecting robotic persuasion. Ultimately, this will be important for enabling human-robot interaction programmers to be in control of their robots: to reduce the persuasiveness of robots in potentially dangerous situations, or make robots more convincing when appropriate.