是什么驱动你与机器人互动？：真实环境中用户动机对机器人的作用
What Drives You to Interact?: The Role of User Motivation for a Robot in the Wild
AI总结：
通过在商场部署自主对话机器人并分析视频，研究识别了用户互动动机、站位与交互流畅度模式，表明动机感知设计可改善真实场景HRI体验。
摘要：
本文旨在理解用户动机如何影响真实环境中的人机交互（HRI）。为探究这一问题，我们开展了一项实地研究：在一家商场内部署一台完全自主的对话机器人，持续两天。通过逐段视频分析，我们识别出五种交互流畅度模式（Smooth、Awkward、Active、Messy和Quiet）、四类用户与机器人互动的动机（Function、Experiment、Curiosity和Education），以及用户相对于机器人的站位。我们进一步分析了这些动机和站位如何影响交互流畅度。研究结果表明，将用户的动机类型纳入机器人行为设计，可提升真实HRI场景中的交互流畅度、参与度和用户满意度。
英文摘要：
In this paper, we aim to understand how user motivation shapes human-robot interaction (HRI) in the wild. To explore this, we conducted a field study by deploying a fully autonomous conversational robot in a shopping mall over two days. Through sequential video analysis, we identified five patterns of interaction fluency (Smooth, Awkward, Active, Messy, and Quiet), four types of user motivation for interacting with the robot (Function, Experiment, Curiosity, and Education), and user positioning towards the robot. We further analyzed how these motivations and positioning influence interaction fluency. Our findings suggest that incorporating users' motivation types into the design of robot behavior can enhance interaction fluency, engagement, and user satisfaction in real-world HRI scenarios.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
