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Going into the wild in child-robot interaction studies: issues in social robotic development

机译:儿童机器人互动研究中的狂野:社交机器人发展中的问题

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As robots move into more human centric environments we require methods to develop robots that can naturally interact with humans. Doing so requires testing in the real-world and addressing multidisciplinary challenges. Our research is focused on child-robot interaction which includes very young children, for example toddlers, and children diagnosed with autism. More traditional forms of human-robot communication, such as speech or gesture recognition, may not be appropriate with these users, where as touch may help to provide a more natural and appropriate means of communication for such instances. In this paper, we present our findings on these topics obtained from a project involving a spherical robot that acquires information regarding natural touch from analysing sensory patterns over-time to characterize the information. More specifically, from this project we have derived important factors for future consideration, we describe our iterative experimental methodology of testing in and out of the 'wild' (lab based and real world), and outline discoveries that were made by doing so.
机译:随着机器人进入以人类为中心的环境,我们需要开发能够与人类自然互动的机器人的方法。这样做需要在现实世界中进行测试并解决多学科挑战。我们的研究集中在儿童与机器人的交互上,其中包括年幼的孩子,例如学步儿童和被诊断出患有自闭症的孩子。对于这些用户而言,诸如语音或手势识别之类的更传统的人机通信形式可能不适合这些用户,因为触摸可能有助于为此类实例提供更自然和合适的通信方式。在本文中,我们介绍了从一个涉及球形机器人的项目中获得的关于这些主题的发现,该球形机器人通过随着时间的推移分析感官模式来表征信息,从而获取有关自然触觉的信息。更具体地说,我们从该项目中得出了一些重要因素供以后考虑,我们描述了在“野生”(基于实验室和真实世界)中进行测试的迭代实验方法,并概述了这样做的发现。

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