UE-HRI dataset

Atef Ben-Youssef, Chloé Clavel and Slim Essid

UE-HRI is a new dataset collected for the study of user engagement in spontaneous Human-Robot Interactions (HRI).

UE-HRI dataset consists of recordings of humans interacting with the social robot Pepper. It targets the diverse social signals that are involved in user engagement, considering a wide range of heterogeneous sensors: a microphone array, cameras, depth sensors, sonars, lasers, along with user feedback captured through Pepper’s touch screen.

All data streams available on Pepper are packaged in the open-source Robot Operating System (ROS) framework . Each stream is passed into a message (called ROS topic) and packaged together into a ROSbag file. All streams are indexed using the robot timestamps to avoid synchronisation issues.

Pepper robot

Pepper humanoid robot: 3D visualisation of sensors position (sonars, laser, front, bottom and depth cameras) using rviz


These data are available to download for research purpose only (not to disseminate):

Your use of the dataset is subject to the terms and conditions. Please read them carefully before registration. Your use of the dataset is conditional upon your acceptance of these terms and conditions.


If you use this dataset, please cite:

Atef Ben Youssef, Chloé Clavel, Slim Essid, Miriam Bilac, Marine Chamoux, and Angelica Lim,
“UE-HRI: A New Dataset for the Study of User Engagement in Spontaneous Human-Robot Interactions”,
in ACM International Conference on Multimodal Interaction, Glasgow, Scotland, Nov. 2017.

 author = {Ben-Youssef, Atef and Clavel, Chlo{\'e} and Essid, Slim and Bilac, Miriam and Chamoux, Marine and Lim, Angelica},
 title = {UE-HRI: A New Dataset for the Study of User Engagement in Spontaneous Human-robot Interactions},
 booktitle = {Proceedings of the 19th ACM International Conference on Multimodal Interaction},
 series = {ICMI 2017},
 year = {2017},
 isbn = {978-1-4503-5543-8},
 location = {Glasgow, UK},
 pages = {464--472},
 numpages = {9},
 url = {},
 doi = {10.1145/3136755.3136814},
 acmid = {3136814},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {HRI dataset, in-the-wild, user engagement}

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