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SFU-store-nav: A multimodal dataset for indoor human navigation

This article describes a dataset collected in a set of experiments that involves human participants and a robot. The set of experiments was conducted in the computing science robotics lab in Simon Fraser University, Burnaby, BC, Canada, and its aim is to gather data containing common gestures, movem...

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Autores principales: Zhang, Zhitian, Rhim, Jimin, TaherAhmadi, Mahdi, Yang, Kefan, Lim, Angelica, Chen, Mo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691721/
https://www.ncbi.nlm.nih.gov/pubmed/33294527
http://dx.doi.org/10.1016/j.dib.2020.106539
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author Zhang, Zhitian
Rhim, Jimin
TaherAhmadi, Mahdi
Yang, Kefan
Lim, Angelica
Chen, Mo
author_facet Zhang, Zhitian
Rhim, Jimin
TaherAhmadi, Mahdi
Yang, Kefan
Lim, Angelica
Chen, Mo
author_sort Zhang, Zhitian
collection PubMed
description This article describes a dataset collected in a set of experiments that involves human participants and a robot. The set of experiments was conducted in the computing science robotics lab in Simon Fraser University, Burnaby, BC, Canada, and its aim is to gather data containing common gestures, movements, and other behaviours that may indicate humans’ navigational intent relevant for autonomous robot navigation. The experiment simulates a shopping scenario where human participants come in to pick up items from his/her shopping list and interact with a Pepper robot that is programmed to help the human participant. We collected visual data and motion capture data from 108 human participants. The visual data contains live recordings of the experiments and the motion capture data contains the position and orientation of the human participants in world coordinates. This dataset could be valuable for researchers in the robotics, machine learning and computer vision community.
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spelling pubmed-76917212020-12-07 SFU-store-nav: A multimodal dataset for indoor human navigation Zhang, Zhitian Rhim, Jimin TaherAhmadi, Mahdi Yang, Kefan Lim, Angelica Chen, Mo Data Brief Data Article This article describes a dataset collected in a set of experiments that involves human participants and a robot. The set of experiments was conducted in the computing science robotics lab in Simon Fraser University, Burnaby, BC, Canada, and its aim is to gather data containing common gestures, movements, and other behaviours that may indicate humans’ navigational intent relevant for autonomous robot navigation. The experiment simulates a shopping scenario where human participants come in to pick up items from his/her shopping list and interact with a Pepper robot that is programmed to help the human participant. We collected visual data and motion capture data from 108 human participants. The visual data contains live recordings of the experiments and the motion capture data contains the position and orientation of the human participants in world coordinates. This dataset could be valuable for researchers in the robotics, machine learning and computer vision community. Elsevier 2020-11-18 /pmc/articles/PMC7691721/ /pubmed/33294527 http://dx.doi.org/10.1016/j.dib.2020.106539 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Zhang, Zhitian
Rhim, Jimin
TaherAhmadi, Mahdi
Yang, Kefan
Lim, Angelica
Chen, Mo
SFU-store-nav: A multimodal dataset for indoor human navigation
title SFU-store-nav: A multimodal dataset for indoor human navigation
title_full SFU-store-nav: A multimodal dataset for indoor human navigation
title_fullStr SFU-store-nav: A multimodal dataset for indoor human navigation
title_full_unstemmed SFU-store-nav: A multimodal dataset for indoor human navigation
title_short SFU-store-nav: A multimodal dataset for indoor human navigation
title_sort sfu-store-nav: a multimodal dataset for indoor human navigation
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691721/
https://www.ncbi.nlm.nih.gov/pubmed/33294527
http://dx.doi.org/10.1016/j.dib.2020.106539
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