Abstract
Human-friendly interactive features are preferred for service robots used in emerging areas of robotic applications such as caretaking, health care, assistance, education and entertainment since they are intended to be operated by non-expert users. Humans prefer to use voice instructions, responses, and suggestions in their daily interactions. Such voice instructions and responses often include uncertain spatial descriptors such as “little” and “far”, which have no definitive quantitative meaning. Service robots involve direct interactions with human users through voice communication. Therefore, the ability to effectively quantify the meaning of such uncertain spatial descriptors is necessary for human-friendly service robots. This paper proposes a novel method to quantify the uncertain spatial descriptors in navigational instructions based on the current environmental setting and the influential notions conveyed by the pointing gestures that accompany voice instructions. The uncertain spatial descriptors are quantified by a fuzzy inference system that evaluates the spatial parameters of the current environment and the influential notions conveyed by pointing gestures, if available. According to the obtained experimental results, the proposed method is capable of improving the quantification ability of uncertain spatial descriptors by robots.
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This work was supported by the University of Moratuwa Senate Research Grant No. SRC/CAP/2017/03.
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Muthugala, M.A.V.J., Srimal, P.H.D.A.S. & Jayasekara, A.G.B.P. Improving robot’s perception of uncertain spatial descriptors in navigational instructions by evaluating influential gesture notions. J Multimodal User Interfaces 15, 11–24 (2021). https://doi.org/10.1007/s12193-020-00328-w
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DOI: https://doi.org/10.1007/s12193-020-00328-w