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Collision-free trajectory planning for robotic assembly of lightweight structures

This research presents a trajectory planning approach for robotic assembly of lightweight structures for COVID-19 healthcare facilities. The prefabricated building components of COVID-19 healthcare facilities have nonnegligible volume, where the crux of the scientific question lies in how to incorpo...

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Detalles Bibliográficos
Autores principales: Shu, Jiangpeng, Li, Wenhao, Gao, Yifan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345853/
https://www.ncbi.nlm.nih.gov/pubmed/35937900
http://dx.doi.org/10.1016/j.autcon.2022.104520
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author Shu, Jiangpeng
Li, Wenhao
Gao, Yifan
author_facet Shu, Jiangpeng
Li, Wenhao
Gao, Yifan
author_sort Shu, Jiangpeng
collection PubMed
description This research presents a trajectory planning approach for robotic assembly of lightweight structures for COVID-19 healthcare facilities. The prefabricated building components of COVID-19 healthcare facilities have nonnegligible volume, where the crux of the scientific question lies in how to incorporate geometry-based collision checks in trajectory planning. This research developed an algorithm that refines the RRT* (Rapidly-exploring Random Tree-Star) algorithm to enable the detour of a planned trajectory based on the geometry of prefabricated components to prevent collisions. Testing of the approach reveals that it has satisfactory collision-avoiding and trajectory-smoothing performance, and is time- and labour-saving compared with the traditional human method. The satisfactory results highlight the practical implication of this research, where robots can replace human labour and contribute to the mitigation of COVID-19 spread on construction sites. The subsequent research will investigate the use of a collaborative robot to screw bolt connections after the components are assembled at locations.
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spelling pubmed-93458532022-08-03 Collision-free trajectory planning for robotic assembly of lightweight structures Shu, Jiangpeng Li, Wenhao Gao, Yifan Autom Constr Article This research presents a trajectory planning approach for robotic assembly of lightweight structures for COVID-19 healthcare facilities. The prefabricated building components of COVID-19 healthcare facilities have nonnegligible volume, where the crux of the scientific question lies in how to incorporate geometry-based collision checks in trajectory planning. This research developed an algorithm that refines the RRT* (Rapidly-exploring Random Tree-Star) algorithm to enable the detour of a planned trajectory based on the geometry of prefabricated components to prevent collisions. Testing of the approach reveals that it has satisfactory collision-avoiding and trajectory-smoothing performance, and is time- and labour-saving compared with the traditional human method. The satisfactory results highlight the practical implication of this research, where robots can replace human labour and contribute to the mitigation of COVID-19 spread on construction sites. The subsequent research will investigate the use of a collaborative robot to screw bolt connections after the components are assembled at locations. Elsevier B.V. 2022-10 2022-08-03 /pmc/articles/PMC9345853/ /pubmed/35937900 http://dx.doi.org/10.1016/j.autcon.2022.104520 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Shu, Jiangpeng
Li, Wenhao
Gao, Yifan
Collision-free trajectory planning for robotic assembly of lightweight structures
title Collision-free trajectory planning for robotic assembly of lightweight structures
title_full Collision-free trajectory planning for robotic assembly of lightweight structures
title_fullStr Collision-free trajectory planning for robotic assembly of lightweight structures
title_full_unstemmed Collision-free trajectory planning for robotic assembly of lightweight structures
title_short Collision-free trajectory planning for robotic assembly of lightweight structures
title_sort collision-free trajectory planning for robotic assembly of lightweight structures
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345853/
https://www.ncbi.nlm.nih.gov/pubmed/35937900
http://dx.doi.org/10.1016/j.autcon.2022.104520
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