注意力吸引行为生成与识别的三层模型

Osamu Sugiyama, T. Kanda, M. Imai, H. Ishiguro, N. Hagita
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引用次数: 13

摘要

本文提出了一个三层的注意力吸引行为生成和识别模型。该模型使机器人能够识别人的注意力吸引行为,并对人进行注意力吸引行为。它由三层组成:PSM(指向空间模型)、RTM(引用项模型)和OPM(对象属性模型)。PSM将指向手势与参考项关联起来,RTM将位置关系与参考项关联起来,OPM将其他补充口头线索与参考项关联起来。我们在人形机器人Robovie中实现了该模型,并通过实验验证了其有效性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Three-Layer Model for Generation and Recognition of Attention-Drawing Behavior
This paper presents a three-layer model for generation and recognition of attention-drawing behavior. The model enables a robot to recognize people's attention-drawing behavior as well as to perform attention-drawing behavior to people. It consists of three layers: the PSM (pointing space model), the RTM (reference term model), and the OPM (object property model). The PSM associates the pointing gesture with a reference term, the RTM associates positional relationships with a reference term, and the OPM associates other supplemental verbal cues with a reference term. We implemented the model in a humanoid robot, Robovie, and verified its effectiveness through an experiment
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