Community Embedded Robotics: Vid2Real An Online Video Dataset about Perceived Social Intelligence in Human Robot Encounters

Introduction This dataset was gathered during the Vid2Real online video-based study, which investigates humans’ perception of robots' intelligence in the context of an incidental Human-Robot encounter. The dataset contains participants' questionnaire responses to four video study conditions, namely Baseline, Verbal, Body language, and Body language + Verbal. The videos depict a scenario where a pedestrian incidentally encounters a quadruped robot trying to enter a building. The robot uses verbal commands or body language to try to ask for help from the pedestrian in different study conditions. The differences in the conditions were manipulated using the robot’s verbal and expressive movement functionalities. Dataset Purpose The dataset includes the responses of human subjects about the robots' social intelligence used to validate the hypothesis that robot social intelligence is positively correlated with human compliance in an incidental human-robot encounter context. The video based dataset was also developed to obtain empirical evidence that can be used to design future real-world HRI studies. Dataset Contents Four videos, each corresponding to a study condition. Four sets of Perceived Social Intelligence Scale data. Each set corresponds to one study condition Four sets of compliance likelihood questions, each set include one Likert question and one free-form question One set of Godspeed questionnaire data. One set of Anthropomorphism questionnaire data. A csv file containing the participants demographic data, Likert scale data, and text responses. A data dictionary explaining the meaning of each of the fields in the csv file. Study Conditions There are 4 videos (i.e. study conditions), the video scenarios are as follows. Baseline: The robot walks up to the entrance and waits for the pedestrian to open the door without any additional behaviors. This is also the "control" condition. Verbal: The robot walks up to the entrance, and says ”can you please open the door for me” to the pedestrian while facing the same direction, then waits for the pedestrian to open the door. Body Language: The robot walks up to the entrance, turns its head to look at the pedestrian, then turns its head to face the door, and waits for the pedestrian to open the door. Body Language + Verbal: The robot walks up to the entrance, turns its head to look at the pedestrian, and says ”Can you open the door for me” to the pedestrian, then waits for the pedestrian to open the door. Image showing the Verbal condition. Image showing the Body Language condition. A within-subject design was adopted, and all participants experienced all conditions. The order of the videos, as well as the PSI scales, were randomized. After receiving consent from the participants, they were presented with one video, followed by the PSI questions and the two exploratory questions (compliance likelihood) described above. This set was repeated 4 times, after which the participants would answer their general perceptions of the robot with Godspeed and AMPH questionnaires. Each video was around 20 seconds and the total study time was around 10 minutes. Video as a Study Method A video-based study in human-robot interaction research is a common method for data collection. Videos can easily be distributed via online participant recruiting platforms, and can reach a larger sample than in-person/lab-based studies. Therefore, it is a fast and easy method for data collection for research aiming to obtain empirical evidence. Video Filming The videos were filmed with a first-person point-of-view in order to maximize the alignment of video and real-world settings. The device used for the recording was an iPhone 12 pro, and the videos were shot in 4k 60 fps. For better accessibility, the videos have been converted to lower resolutions. Instruments The questionnaires used in the study include the Perceived Social Intelligence Scale (PSI), Godspeed Questionnaire, and Anthropomorphism Questionnaire (AMPH). In addition to these questionnaires, a 5-point Likert question and a free-text response measuring human compliance were added for the purpose of the video-based study. Participant demographic data was also collected. Questionnaire items are attached as part of this dataset. Human Subjects For the purpose of this project, the participants are recruited through Prolific. Therefore, the participants are users of Prolific. Additionally, they are restricted to people who are currently living in the United States, fluent in English, and have no hearing or visual impairments. No other restrictions were imposed. Among the 385 participants, 194 participants identified as female, and 191 as male, the age ranged from 19 to 75 (M = 38.53, SD = 12.86). Human subjects remained anonymous. Participants were compensated with $4 upon submission approval. This study was reviewed and approved by UT Austin Internal Review Board. Robot The dataset contains data about humans’ perceived social intelligence of a Boston Dynamics’ quadruped robot Spot (Explorer model). The robot was selected because quadruped robots are gradually being adopted to provide services such as delivery, surveillance, and rescue. However, there are still issues or obstacles that robots cannot easily overcome by themselves in which they will have to ask for help from nearby humans. Therefore, it is important to understand how humans react to a quadruped robot that they incidentally encounter. For the purposes of this video-study, the robot operation was semi-autonomous, with the navigation being manually teleoperated by an operator and a few standalone autonomous modules to supplement it. Data Collection The data was collected through Qualtrics, a survey development platform. After the completion of data collection, the data was downloaded as a csv file. Data Quality Control Qualtrics automatically detects bots so any response that is flagged as bots are discarded. All incomplete and duplicate responses were discarded. Data Usage This dataset can be used to conduct a meta-analysis on robots' perceived intelligence. Please note that data is coupled with this study design. Users interested in data reuse will have to assess that this dataset is in line with their study design. Acknowledgement This study was funded through the NSF Award # 2219236GCR: Community-Embedded Robotics: Understanding Sociotechnical Interactions with Long-term Autonomous Deployments.引言 本数据集采集自Vid2Real在线视频研究，该研究旨在探究人类在人机偶遇场景下对机器人智能的感知。数据集包含参与者针对四种视频研究条件的问卷反馈，分别为对照组（Baseline）、语言组（Verbal）、肢体语言组（Body language）以及肢体语言+语言组（Body language + Verbal）。视频呈现的场景为：一名行人偶然遇到一台试图进入建筑的四足机器人，在不同研究条件下，机器人会通过语言指令或肢体语言向行人求助。各条件间的差异通过机器人的语言与表情运动功能进行操控。 数据集用途 数据集包含人类受试者对机器人社交智能的反馈，用于验证以下假设：在人机偶遇场景中，机器人的社交智能与人类依从性呈正相关。该基于视频的数据集还旨在获取实证依据，用于设计未来的真实世界人机交互（Human-Robot Interaction, HRI）研究。 数据集内容 1. 四段视频，分别对应一种研究条件； 2. 四组感知社交智能量表（Perceived Social Intelligence Scale, PSI）数据，每组对应一种研究条件； 3. 四组依从性可能性问题，每组包含1道李克特量表题与1道开放式问题； 4. 1组Godspeed问卷数据； 5. 1组拟人化问卷（Anthropomorphism Questionnaire, AMPH）数据； 6. 1份包含参与者人口统计学数据、李克特量表数据与文本反馈的CSV文件； 7. 一份数据字典，用于说明CSV文件中各字段的含义。 研究条件 本研究共包含四段视频（即四种研究条件），对应场景如下： - 对照组（Baseline）：机器人行至入口处等待行人开门，无任何额外行为，本条件也作为“控制组”； - 语言组（Verbal）：机器人行至入口处，面朝行人说道“麻烦帮我开一下门可以吗？”，随后等待行人开门； - 肢体语言组（Body language）：机器人行至入口处，转头看向行人，随后转头看向大门，等待行人开门； - 肢体语言+语言组（Body language + Verbal）：机器人行至入口处，转头看向行人并说道“麻烦帮我开一下门可以吗？”，随后等待行人开门。 本研究附语言组场景展示图与肢体语言组场景展示图。 本研究采用被试内设计（within-subject design），所有参与者均需完成全部四种条件。视频顺序与PSI量表的呈现顺序均经过随机化处理。 在获得参与者的知情同意后，研究将依次向其播放一段视频、呈现PSI量表问题与前述两道探究性依从性可能性问题，该流程重复四次。随后参与者需填写Godspeed问卷与AMPH问卷，以表达其对机器人的整体感知。 每段视频时长约20秒，整个研究的总时长约为10分钟。 作为研究方法的视频采集 在人机交互研究中，基于视频的研究是一种常用的数据收集方法。视频可通过在线参与者招募平台轻松分发，且相较于线下/实验室研究，能够触达更大的样本量。因此，该方法对于需要获取实证依据的研究而言，是一种高效便捷的数据收集手段。 视频拍摄 视频采用第一人称视角拍摄，以最大化匹配真实场景的视觉体验。录制设备为iPhone 12 Pro，视频以4K 60 fps规格拍摄。为提升可访问性，所有视频均已转换为更低分辨率版本。 研究工具 本研究使用的问卷包括感知社交智能量表（Perceived Social Intelligence Scale, PSI）、Godspeed问卷以及拟人化问卷（Anthropomorphism Questionnaire, AMPH）。除此之外，为适配本视频研究，还新增了一道5点李克特量表题与一道开放式文本题，用于测量人类的依从性。研究同时收集了参与者的人口统计学数据。问卷条目已作为本数据集的一部分附带。 人类受试者 本项目通过Prolific平台招募参与者，因此参与者均为Prolific平台用户。此外，招募限制为：目前居住在美国、英语流利、无听力或视觉障碍的人群，未设置其他限制条件。 本次研究共招募385名参与者，其中194名自认为女性，191名自认为男性；年龄分布为19岁至75岁，均值M=38.53，标准差SD=12.86。 所有人类受试者均保持匿名。参与者在提交的问卷通过审核后，可获得4美元的报酬。 本研究已通过德克萨斯大学奥斯汀分校（UT Austin）内部审查委员会的审查与批准。 机器人 本数据集包含人类受试者对波士顿动力（Boston Dynamics）四足机器人Spot（Explorer型号）的感知社交智能相关数据。选择该机器人的原因在于，四足机器人正逐步被应用于配送、监控、救援等服务场景，但目前仍存在诸多机器人自身难以克服的障碍，需要向附近人类求助。因此，理解人类对偶然遇到的四足机器人的反应具有重要意义。 在本视频研究中，机器人采用半自主操控模式：导航由操作员手动远程操控，辅以少量独立自主模块进行补充。 数据收集 数据通过问卷开发平台Qualtrics收集。数据收集完成后，以CSV文件格式导出。 数据质量控制 Qualtrics可自动检测机器人用户，所有被标记为机器人的响应均已被剔除。同时，所有不完整与重复的响应均已被剔除。 数据使用 本数据集可用于开展关于机器人感知智能的元分析。请注意，本数据集与本研究的设计绑定，有兴趣复用该数据集的用户需评估其是否符合自身的研究设计。 致谢 本研究由美国国家科学基金会（National Science Foundation, NSF）奖项#2219236GCR资助：社区嵌入式机器人：理解长期自主部署中的社会技术交互。