Evidence map›Paper›PMID 36333346›Full record

ArticleScientific data2022

Human mobile robot interaction in the retail environment.

Yuhao Chen, Yue Luo, Chizhao Yang, Mustafa Ozkan Yerebakan, Shuai Hao, Nicolas Grimaldi, Song Li, Read Hayes, Boyi Hu

Abstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yuhao ChenDepartment of Industrial and Systems Engineering, University of Florida, Gainesville, FL, 32611, USA.ORCID 0000-0001-7373-3932
Yue LuoDepartment of Industrial and Systems Engineering, University of Florida, Gainesville, FL, 32611, USA.ORCID 0000-0002-0062-3190
Chizhao YangDepartment of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV, 26506, USA.
Mustafa Ozkan YerebakanDepartment of Industrial and Systems Engineering, University of Florida, Gainesville, FL, 32611, USA.
Shuai HaoDepartment of Industrial and Systems Engineering, University of Florida, Gainesville, FL, 32611, USA.
Nicolas GrimaldiJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, 32611, USA.
Song LiDepartment of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, 32611, USA.
Read HayesHerbert Wertheim College of Engineering FLEX, University of Florida, Gainesville, FL, 32611, USA.
Boyi HuDepartment of Industrial and Systems Engineering, University of Florida, Gainesville, FL, 32611, USA. boyihu@ise.ufl.edu.

Funding

National Science Foundation (NSF) No. 2132936NIOSH CDC HHS T42 OH008673U.S. Department of Health & Human Services | CDC | National Institute for Occupational Safety and Health (NIOSH) T42OH00 8673
6 · The paper itself

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.

Indexed as

RoboticsEnvironmentHumansMotion

Identifiers

PMID36333346
PMCPMC9636163

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.