通过任务训练建立富有成效的人机合作伙伴关系

IF 4.2 Q2 ROBOTICS
Maia Stiber, Yuxiang Gao, R. Taylor, Chien-Ming Huang
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引用次数: 1

摘要

高效的人机合作关系对于将辅助机器人成功融入日常生活至关重要。虽然之前的研究已经探索了在人机交互过程中促进协作的技术,但这里描述的工作旨在在人机交互之前建立富有成效的伙伴关系,利用团队建设活动帮助建立有效的人类团队。通过一项2(群体成员:内群体和外群体)× 3(机器人错误:主任务错误、副任务错误和无错误)的在线研究(N = 62),我们证明了1)非社会任务前练习可以帮助形成内群体关系;2)内组机器人被认为是比外组机器人更好、更忠诚的队友(尽管两者的行为相同);3)参与者在与内部机器人合作时更能容忍负面结果。我们讨论了任务前练习如何作为一种主动的任务失败缓解策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forging Productive Human-Robot Partnerships Through Task Training
Productive human-robot partnerships are vital to successful integration of assistive robots into everyday life. While prior research has explored techniques to facilitate collaboration during human-robot interaction, the work described here aims to forge productive partnerships prior to human-robot interaction, drawing upon team building activities’ aid in establishing effective human teams. Through a 2 (group membership: ingroup and outgroup) × 3 (robot error: main task errors, side task errors, and no errors) online study (N = 62), we demonstrate that 1) a non-social pre-task exercise can help form ingroup relationships; 2) an ingroup robot is perceived as a better, more committed teammate than an outgroup robot (despite the two behaving identically); and 3) participants are more tolerant of negative outcomes when working with an ingroup robot. We discuss how pre-task exercises may serve as an active task failure mitigation strategy.
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来源期刊
ACM Transactions on Human-Robot Interaction
ACM Transactions on Human-Robot Interaction Computer Science-Artificial Intelligence
CiteScore
7.70
自引率
5.90%
发文量
65
期刊介绍: ACM Transactions on Human-Robot Interaction (THRI) is a prestigious Gold Open Access journal that aspires to lead the field of human-robot interaction as a top-tier, peer-reviewed, interdisciplinary publication. The journal prioritizes articles that significantly contribute to the current state of the art, enhance overall knowledge, have a broad appeal, and are accessible to a diverse audience. Submissions are expected to meet a high scholarly standard, and authors are encouraged to ensure their research is well-presented, advancing the understanding of human-robot interaction, adding cutting-edge or general insights to the field, or challenging current perspectives in this research domain. THRI warmly invites well-crafted paper submissions from a variety of disciplines, encompassing robotics, computer science, engineering, design, and the behavioral and social sciences. The scholarly articles published in THRI may cover a range of topics such as the nature of human interactions with robots and robotic technologies, methods to enhance or enable novel forms of interaction, and the societal or organizational impacts of these interactions. The editorial team is also keen on receiving proposals for special issues that focus on specific technical challenges or that apply human-robot interaction research to further areas like social computing, consumer behavior, health, and education.
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