Requirements for Robotic Interpretation of Social Signals xe2x80x9cin the Wildxe2x80x9d: Insights from Diagnostic Criteria of Autism Spectrum Disorder The last few decades have seen widespread advances in technological means to characterise observable aspects of human behaviour such as gaze or posture. Among others, these developments have also led to significant advances in social robotics. At the same time, however, social robots are still largely evaluated in idealised or laboratory conditions, and it remains unclear whether the technological progress is sufficient to let such robots move xe2x80x9cinto the wildxe2x80x9d. In this paper, we characterise the problems that a social robot in the real world may face, and review the technological state of the art in terms of addressing these. We do this by considering what it would entail to automate the diagnosis of Autism Spectrum Disorder (ASD). Just as for social robotics, ASD diagnosis fundamentally requires the ability to characterise human behaviour from observable aspects. However, therapists provide clear criteria regarding what to look for. As such, ASD diagnosis is a situation that is both relevant to realworld social robotics and comes with clear metrics. Overall, we demonstrate that even with relatively clear therapistprovided criteria and current technological progress, the need to interpret covert behaviour cannot yet be fully addressed. Our discussions have clear implications for ASD diagnosis, but also for social robotics more generally. For ASD diagnosis, we provide a classification of criteria based on whether or not they depend on covert information and highlight presentday possibilities for supporting therapists in diagnosis through technological means. For social robotics, we highlight the fundamental role of covert behaviour, show that the current stateoftheart is unable to characterise this, and emphasise that future research should tackle this explicitly in realistic settings.

Designing a Socially Assistive Robot for LongTerm InHome Use for Children with Autism Spectrum Disorders Socially assistive robotics (SAR) research has shown great potential for supplementing and augmenting therapy for children with autism spectrum disorders (ASD). However, the vast majority of SAR research has been limited to shortterm studies in highly controlled environments. The design and development of a SAR system capable of interacting autonomously it in situ for long periods of time involves many engineering and computing challenges. This paper presents the design of a fully autonomous SAR system for longterm, inhome use with children with ASD. We address design decisions based on robustness and adaptability needs, discuss the development of the robotu0027s character and interactions, and provide insights from the monthlong, inhome data collections with children with ASD. This work contributes to a larger research program that is exploring how SAR can be used for enhancing the social and cognitive development of children with ASD.