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Capturing Expertise: Developing Interaction Content for a Robot Through Teleoperation by Domain Experts

机译:捕获专业知识:通过域专家通过遥操作开发机器人的互动内容

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摘要

The development of humanlike service robots which interact socially raises a new question: how can we create good interaction content for such robots? Domain experts specializing in the target service have the knowledge for making such content. Yet, while they can easily engage in good face-to-face interactions, we found it difficult for them to prepare conversational content for a robot in written form. Instead, we propose involving experts as teleoperators in a short-cycle iterative development process in which the expert develops content, teleoperates a robot using that content, and then revises the content based on that interaction. We propose a software system and design guidelines to enable such an iterative design process. To validate these solutions, we conducted a comparison experiment in the field, with a teleoperated robot acting as a guide at a tourist information center in Nara, Japan. The results showed that our system and guidelines enabled domain experts with no robotics background to create better interaction content and conduct better interactions than domain experts without our system.
机译:人类服务机器人的发展,社会互动提出了一个新问题:我们如何为这些机器人创造良好的互动内容?域专家专门从事目标服务具有制定此类内容的知识。然而,虽然它们可以轻松地参与良好的面对面的互动,但我们发现他们很难以书面形式为机器人做好准备的会话内容。相反,我们建议在专家开发内容的短期迭代开发过程中涉及专家作为漫游者,使用该内容来联市机器人,然后根据该交互来修改内容。我们提出了一种软件系统和设计指南,以实现这种迭代设计过程。为了验证这些解决方案,我们在该领域进行了一个比较实验,通过漫步的机器人作为日本奈良的旅游信息中心作为指导。结果表明,我们的系统和准则使域专家没有机器人背景,创造更好的互动内容,并在没有我们的系统的情况下开展比领域专家更好的互动。

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