Nhi Tran* and Snehesh Shrestha*
*Equal Contribution
John Hopkins University and University of Maryland College Park
Abstract
Crowdsourcing data for Human-Robot Interaction (HRI) research remains a challenge, requiring scalable, flexible, and immersive methods to collect meaningful interaction data. This paper introduces CrowdHRI, a novel approach to gamify HRI data collection through a multiplayer mixed reality (MR) game. The proposed system integrates a web server and Unity-based client architecture, enabling users to schedule or join sessions dynamically. Through immersive MR, CrowdHRI offers realistic environments and supports customizable experimental setups, gathering high-fidelity data on human-robot interactions. The system includes automated metrics to capture interaction quality, alongside a robust data science framework for analysis. By addressing the limitations of existing platforms—such as restricted scalability and interaction fidelity CrowdHRI enables a wide range of experimental conditions and advances the field of HRI research.
We will release the full source code under the MIT License at CrowdHRI website to support future HRI research.
Acknowledgments
Special thanks to Dr. Jeremy Marvel of the National Institute of Standards and Technology (NIST) for his support and advice.
Bibtex
@inproceedings{transhrestha2025crowdhri,
title = {{CrowdHRI}: Gamifying HRI Data Collection as a Multiplayer Mixed Reality Game},
author = {Nhi Tran, Snehesh Shrestha},
year = {2025},
booktitle={2025 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI)}
}License
CrowdHRI will be freely available for non-commercial and research use and may be redistributed under the MIT License. For commercial licensing, or if you have any questions, please get in touch with me at snehesh@umd.edu.