Leveraging people's everyday skill sets for interaction with robots

利用人们的日常技能与机器人互动

• 批准号: 402562-2011
• 负责人: Young, James
• 金额: $ 1.38万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=573320
• 关键词: Leveraging; people; everyday; skill; sets

As advancing robotic technology begins to enter the everyday world of the general public, for example as utility or health-care robots, it is important to consider how people and robots will communicate, and how people will issue commands or extract data. Unfortunately, interacting with robots can be very difficult and generally requires training and expertise. As many robot users may not be robotics experts, I believe that it will be important to make interacting with robots as easy as interacting with other people. In this work we move away from robot-centric command consoles, and built robots that enable people to accomplish complex robot interaction tasks using their existing everyday (non-robot oriented) abilities and work practices (e.g., ability to teach others and give directions, or skills working with animals). We further aim to develop a stronger understanding of which existing social skills and structures robots can leverage in their designs, how they impact environments they integrate into, and how impact can be influenced by design. As one component of this work we will study which everyday tasks robots could assist with, and which existing interaction structures a robot could integrate into. Second, we will develop new robotic implementations which serve as proofs-of-concepts for incorporating existing human interaction techniques into robotic behaviors and designs. Finally, we will place our new technologies into real-world environments and observe people working with them as a means to test our designs and to further inform future interfaces. The resulting new human-robot interfaces will be among the first practical robot implementations that are designed to integrate naturally into existing everyday scenarios and social structures, and the in-context evaluations will provide new insight into how people interact with robots in real-world settings.

随着先进的机器人技术开始进入普通公众的日常世界，例如作为公用事业或医疗保健机器人，重要的是考虑人类和机器人将如何沟通，以及人们将如何发布命令或提取数据。不幸的是，与机器人互动可能非常困难，通常需要培训和专业知识。由于许多机器人用户可能不是机器人专家，我认为让与机器人互动像与其他人互动一样容易将是很重要的。 在这项工作中，我们不再以机器人为中心，而是构建了机器人，使人们能够使用现有的日常(非面向机器人的)能力和工作实践(例如，教导他人和给出方向的能力，或与动物打交道的技能)来完成复杂的机器人交互任务。我们的进一步目标是更好地理解机器人在设计中可以利用哪些现有的社交技能和结构，它们如何影响它们融入的环境，以及影响如何受到设计的影响。 作为这项工作的一个组成部分，我们将研究机器人可以协助哪些日常任务，以及机器人可以整合到哪些现有的交互结构中。其次，我们将开发新的机器人实现，作为将现有的人类交互技术整合到机器人行为和设计中的概念证明。最后，我们将把我们的新技术应用到真实环境中，并观察使用它们的人，以此作为测试我们的设计并进一步通知未来界面的一种手段。 由此产生的新的人-机器人界面将是第一批实用的机器人实现之一，旨在自然地融入现有的日常场景和社会结构，情景评估将为人们在现实世界中如何与机器人互动提供新的见解。