Human Mobile Robot Interaction in the Retail Environment

Details

• Personal Author:
  Chen Y ; Grimaldi N ; Hao S ; Hayes R ; Hu B ; Li S ; Luo Y ; Yang C ; Yerebakan MO
• Description:
  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. 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. [Description provided by NIOSH]
• Subjects:
  Environmental Exposure Occupational Health Safety
• Keywords:
  Environmental Exposure Humans Motion Studies Robotics Sociological Factors Wholesale And Retail Trade
• ISSN:
  2052-4463
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Florida ; North Carolina ; OSHA Region 3 ; OSHA Region 4 ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  9
• Issue:
  1
• NIOSHTIC Number:
  nn:20066323
• Citation:
  Sci Data 2022 Nov; 9(1):673
• Contact Point Address:
  Boyi Hu, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, 32611
• Email:
  boyihu@ise.ufl.edu
• Federal Fiscal Year:
  2023
• Performing Organization:
  University of North Carolina, Chapel Hill
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Scientific Data
• End Date:
  20270630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:54cdd652c9f6437c78525e5cce65ccbbe3b764101d97f1e7a11723d8bd9ee52676350ed3a8bdd7bfc93dbf9e5d917d56cf00ed15148551fad9a2eb6274286756
• Download URL:
  https://stacks.cdc.gov/view/cdc/212793/cdc_212793_DS1.pdf
• File Type:
  [PDF - 2.73 MB ]