首页> 外文会议>ACM/IEEE International Conference on Human-Robot Interaction >From One to Another: How Robot-Robot Interaction Affects Users' Perceptions Following a Transition Between Robots
【24h】

From One to Another: How Robot-Robot Interaction Affects Users' Perceptions Following a Transition Between Robots

机译:从一个到另一个:机器人之间的转换后,机器人与机器人的交互如何影响用户的感知

获取原文

摘要

Human-robot interactions that involve multiple robots are becoming common. It is crucial to understand how multiple robots should transfer information and transition users between them. To investigate this, we designed a $3 imes 3$ mixed-design study in which participants took part in a navigation task. Participants interacted with a stationary robot who summoned a functional (not explicitly social) mobile robot to guide them. Each participant experienced the three types of robot-robot interaction: representative (the stationary robot spoke to the participant on behalf of the mobile robot), direct (the stationary robot delivered the request to the mobile robot in a straightforward manner), and social (the stationary robot delivered the request to the mobile robot in a social manner). Each participant witnessed only one type of robot-robot communication: silent (the robots covertly communicated), explicit (the robots acknowledged that they were communicating), or reciting (the stationary robot said the request aloud). Our results show that it is possible to instill socialness in and improve likability of a functional robot by having a social robot interact socially with it. We also found that covertly exchanging information is less desirable than reciting information aloud.
机译:涉及多个机器人的人机交互正在变得越来越普遍。了解多个机器人应如何传递信息并在它们之间转换用户至关重要。为了对此进行调查,我们设计了一个 $ 3 \ \ times \ 3 $ 参与者参加导航任务的混合设计研究。参与者与固定机器人进行了互动,后者会召唤功能性(而非明确社交的)移动机器人来指导他们。每个参与者都经历了三种机器人与机器人的交互:代表(固定机器人代表移动机器人与参与者讲话),直接(固定机器人将请求直接传递给移动机器人)和社交(固定机器人以社交方式将请求传递给了移动机器人)。每个参与者只目睹了一种机器人与机器人的通信:静默(机器人秘密通信),显式(机器人承认他们正在通信)或背诵(静止的机器人大声说出了请求)。我们的结果表明,通过让社交机器人与其进行社交互动,可以向社交机器人灌输社交性,并提高其功能。我们还发现,秘密地交换信息比大声地朗诵信息更不可取。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号