Modeling communicative behaviors for object references in human-robot interaction
Modeling communicative behaviors for object references in human-robot interaction
复制标题
对人机交互中对象引用的通信行为进行建模
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
B. Scassellati
中科院分区：
文献类型：
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作者：
H. Admoni;Thomas Weng;B. Scassellati
本文提出了一种模型，该模型利用机器人的言语和非言语行为，成功地向人类伙伴传达物体指称。这个模型借鉴了计算机视觉、人机交互和认知心理学，模拟了场景的低级和高级特征如何吸引用户的注意力。然后，它选择最合适的机器人行为，在最大程度上提高用户理解正确物体指称的可能性，同时将行为成本降至最低。我们为该模型提出了一个通用的计算框架，然后描述了在人机协作中的一种具体实现。最后，我们在两次人工评估中分析了该模型的性能——一次是基于视频的（75名参与者），一次是现场的（20名参与者）——并证明该系统能够预测出正确的行为，以实现成功的物体指称。
This paper presents a model that uses a robot's verbal and nonverbal behaviors to successfully communicate object references to a human partner. This model, which is informed by computer vision, human-robot interaction, and cognitive psychology, simulates how low-level and high-level features of the scene might draw a user's attention. It then selects the most appropriate robot behavior that maximizes the likelihood that a user will understand the correct object reference while minimizing the cost of the behavior. We present a general computational framework for this model, then describe a specific implementation in a human-robot collaboration. Finally, we analyze the model's performance in two human evaluations-one video-based (75 participants) and one in person (20 participants)-and demonstrate that the system predicts the correct behaviors to perform successful object references.