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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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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. |
format | Online Article Text |
id | pubmed-9345853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
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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