Abstract

As technology advances, Human-Robot Interaction (HRI) is boosting overall system efficiency and productivity. However, allowing robots to be present closely with humans will inevitably put higher demands on precise human motion tracking and prediction. Datasets that contain both humans and robots operating in the shared space are receiving growing attention as they may facilitate a variety of robotics and human-systems research. Datasets that track HRI with rich information other than video images during daily activities are rarely seen. In this paper, we introduce a novel dataset that focuses on social navigation between humans and robots in a future-oriented Wholesale and Retail Trade (WRT) environment (https://uf-retail-cobot-dataset.github.io/). Eight participants performed the tasks that are commonly undertaken by consumers and retail workers. More than 260 minutes of data were collected, including robot and human trajectories, human full-body motion capture, eye gaze directions, and other contextual information. Comprehensive descriptions of each category of data stream, as well as potential use cases are included. Furthermore, analysis with multiple data sources and future directions are discussed.

Measurement(s)

Robot and human trajectories, human full-body motion capture, and eye gaze directions.

Technology Type(s)

Mobile robot, inertial measurement unit-based motion capture system, and eye tracker.

Details

Title
Human mobile robot interaction in the retail environment
Author
Chen, Yuhao 1   VIAFID ORCID Logo  ; Luo, Yue 1   VIAFID ORCID Logo  ; Yang, Chizhao 2 ; Yerebakan, Mustafa Ozkan 1 ; Hao, Shuai 1 ; Grimaldi, Nicolas 3 ; Li, Song 4 ; Hayes, Read 5 ; Hu, Boyi 1 

1  University of Florida, Department of Industrial and Systems Engineering, Gainesville, USA (GRID:grid.15276.37) (ISNI:0000 0004 1936 8091) 
2  West Virginia University, Department of Mechanical and Aerospace Engineering, Morgantown, USA (GRID:grid.268154.c) (ISNI:0000 0001 2156 6140) 
3  University of Florida, J. Crayton Pruitt Family Department of Biomedical Engineering, Gainesville, USA (GRID:grid.15276.37) (ISNI:0000 0004 1936 8091) 
4  University of Florida, Department of Computer and Information Science and Engineering, Gainesville, USA (GRID:grid.15276.37) (ISNI:0000 0004 1936 8091) 
5  University of Florida, Herbert Wertheim College of Engineering FLEX, Gainesville, USA (GRID:grid.15276.37) (ISNI:0000 0004 1936 8091); Loss Prevention Research Council, Gainesville, USA (GRID:grid.15276.37) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41597-022-01802-8
ProQuest document ID
2731952566
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.