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

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.

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