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    Safety experiments for small robots investigating the potential of soft materials in mitigating the harm to the head due to impacts

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    Safety experiments for small robots investigating the potential of soft materials in mitigating the harm to the head due to impacts.pdf (1.146Mb)
    Date
    2019-05-01
    Author
    Alhaddad, Ahmad Yaser
    Cabibihan, John John
    Hayek, Ahmad
    Bonarini, Andrea
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    Abstract
    There is a growing interest in social robots to be considered in the therapy of children with autism due to their effectiveness in improving the outcomes. However, children on the spectrum exhibit challenging behaviors that need to be considered when designing robots for them. A child could involuntarily throw a small social robot during meltdown and that could hit another person’s head and cause harm (e.g. concussion). In this paper, the application of soft materials is investigated for its potential in attenuating head’s linear acceleration upon impact. The thickness and storage modulus of three different soft materials were considered as the control factors while the noise factor was the impact velocity. The design of experiments was based on Taguchi method. A total of 27 experiments were conducted on a developed dummy head setup that reports the linear acceleration of the head. ANOVA tests were performed to analyze the data. The findings showed that the control factors are not statistically significant in attenuating the response. The optimal values of the control factors were identified using the signal-to-noise (S/N) ratio optimization technique. Confirmation tests at the optimal parameters (e.g. thickness of 3 mm or 5 mm) showed better responses as compared to other conditions. Designers of social robots should consider the application of soft materials to their designs as it helps in reducing the potential harm to the head.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85064662516&origin=inward
    DOI/handle
    http://dx.doi.org/10.1007/s42452-019-0467-7
    http://hdl.handle.net/10576/49605
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    • Mechanical & Industrial Engineering [‎1499‎ items ]

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