生态动态实验中的HRI:基于GEE语料库的Emox机器人方法

Leslie Guillaume, V. Aubergé, Romain Magnani, Frédéric Aman, Cecile Cottier, Y. Sasa, Christian Wolf, Florian Nebout, N. Neverova, Nicolas Bonnefond, Amaury Nègre, Liliya Tsvetanova, Maxence Girard-Rivier
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引用次数: 7

摘要

作为人机交互项目的一部分,手势模式是众多交流方式之一。为了开发与智能家庭管家机器人相关的手势识别系统,我们的方法是基于一个类似智商游戏的绿野仙踪实验,在机器人作为裁判的生态环境中收集自发和隐含产生的手势。将这些手势与明确生成的手势进行比较,以确定相关的手势本体。这一初步的定性分析将成为构建大数据语料库的基础,以优化手势词典的接受度,并与“社会情感胶水”动态保持一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HRI in an ecological dynamic experiment: The GEE corpus based approach for the Emox robot
As part of a human-robot interaction project, the gestural modality is one of many ways to communicate. In order to develop a relevant gesture recognition system associated to a smart home butler robot, our methodology is based on an IQ game-like Wizard of Oz experiment to collect spontaneous and implicitly produced gestures in an ecological context where the robot is the referee. These gestures are compared with explicitly produced gestures to determine a relevant ontology of gestures. This preliminary qualitative analysis will be the base to build a big data corpus in order to optimize acceptance of the gesture dictionary in coherence with the “socio-affective glue” dynamics.
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