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机器人眼睛在人机交互中作为预测线索的潜力——一项眼动追踪研究

The potential of robot eyes as predictive cues in HRI-an eye-tracking study.

作者信息

Onnasch Linda, Schweidler Paul, Schmidt Helena

机构信息

Technische Universität Berlin, Berlin, Germany.

HFC Human-Factors-Consult GmbH, Berlin, Germany.

出版信息

Front Robot AI. 2023 Jul 28;10:1178433. doi: 10.3389/frobt.2023.1178433. eCollection 2023.

Abstract

Robots currently provide only a limited amount of information about their future movements to human collaborators. In human interaction, communication through gaze can be helpful by intuitively directing attention to specific targets. Whether and how this mechanism could benefit the interaction with robots and how a design of predictive robot eyes in general should look like is not well understood. In a between-subjects design, four different types of eyes were therefore compared with regard to their attention directing potential: a pair of arrows, human eyes, and two anthropomorphic robot eye designs. For this purpose, 39 subjects performed a novel, screen-based gaze cueing task in the laboratory. Participants' attention was measured using manual responses and eye-tracking. Information on the perception of the tested cues was provided through additional subjective measures. All eye models were overall easy to read and were able to direct participants' attention. The anthropomorphic robot eyes were most efficient at shifting participants' attention which was revealed by faster manual and saccadic reaction times. In addition, a robot equipped with anthropomorphic eyes was perceived as being more competent. Abstract anthropomorphic robot eyes therefore seem to trigger a reflexive reallocation of attention. This points to a social and automatic processing of such artificial stimuli.

摘要

目前,机器人向人类协作伙伴提供的关于其未来动作的信息非常有限。在人际互动中,通过目光交流直观地将注意力引向特定目标会有所帮助。这种机制是否以及如何有益于与机器人的互动,以及一般而言预测性机器人眼睛的设计应该是怎样的,目前还不太清楚。因此,在一项被试间设计中,对四种不同类型的眼睛在引导注意力方面的潜力进行了比较:一对箭头、人类眼睛以及两种拟人化机器人眼睛设计。为此,39名被试在实验室中执行了一项基于屏幕的新型目光提示任务。通过手动反应和眼动追踪来测量参与者的注意力。通过额外的主观测量提供了关于对测试提示的感知信息。所有眼睛模型总体上都易于识别,并且能够引导参与者的注意力。拟人化机器人眼睛在转移参与者注意力方面效率最高,这通过更快的手动反应时间和扫视反应时间得以体现。此外,配备拟人化眼睛的机器人被认为更有能力。因此,抽象的拟人化机器人眼睛似乎会引发注意力的反射性重新分配。这表明对这种人工刺激存在社会和自动加工过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfd5/10416260/014e847e581d/frobt-10-1178433-g001.jpg

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