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A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing
The case of dual manipulators with shared workspace, asynchronous manufacturing tasks, and independent objects is named a dual manipulator cooperative manufacturing system, which requires collision-free path planning as a vital issue in terms of safety and efficiency. This paper combines the mathema...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003517/ https://www.ncbi.nlm.nih.gov/pubmed/35408116 http://dx.doi.org/10.3390/s22072502 |
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author | Su, Chang Xu, Jianfeng |
author_facet | Su, Chang Xu, Jianfeng |
author_sort | Su, Chang |
collection | PubMed |
description | The case of dual manipulators with shared workspace, asynchronous manufacturing tasks, and independent objects is named a dual manipulator cooperative manufacturing system, which requires collision-free path planning as a vital issue in terms of safety and efficiency. This paper combines the mathematical modeling method with the time sampling method in the classification of robot path-planning algorithms. Through this attempt we can achieve an optimal local search path during each sampling period interval. Our strategy is to build the corresponding non-linear optimization functions set based on the motion characteristics of the dual manipulator system. In this way, the path-planning problem can be turned into a purely mathematical problem of solving the non-linear optimization programming equations set. The spatial geometric analysis is used to linearize the predicted dual-manipulator minimum distance equation, thus linearizing the non-linear optimization equations set. Finally, this system of linear optimization equations will be mapped directly into a virtual Euclidean space and then solved intuitively using the spatial geometry theory. By simulation and comparing with the previous strategies, we find that the planning results of the newly proposed planning strategy are smoother and have shorter deviations as well as a higher algorithmic efficiency in terms of spatial geometric properties. |
format | Online Article Text |
id | pubmed-9003517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90035172022-04-13 A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing Su, Chang Xu, Jianfeng Sensors (Basel) Article The case of dual manipulators with shared workspace, asynchronous manufacturing tasks, and independent objects is named a dual manipulator cooperative manufacturing system, which requires collision-free path planning as a vital issue in terms of safety and efficiency. This paper combines the mathematical modeling method with the time sampling method in the classification of robot path-planning algorithms. Through this attempt we can achieve an optimal local search path during each sampling period interval. Our strategy is to build the corresponding non-linear optimization functions set based on the motion characteristics of the dual manipulator system. In this way, the path-planning problem can be turned into a purely mathematical problem of solving the non-linear optimization programming equations set. The spatial geometric analysis is used to linearize the predicted dual-manipulator minimum distance equation, thus linearizing the non-linear optimization equations set. Finally, this system of linear optimization equations will be mapped directly into a virtual Euclidean space and then solved intuitively using the spatial geometry theory. By simulation and comparing with the previous strategies, we find that the planning results of the newly proposed planning strategy are smoother and have shorter deviations as well as a higher algorithmic efficiency in terms of spatial geometric properties. MDPI 2022-03-24 /pmc/articles/PMC9003517/ /pubmed/35408116 http://dx.doi.org/10.3390/s22072502 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Su, Chang Xu, Jianfeng A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing |
title | A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing |
title_full | A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing |
title_fullStr | A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing |
title_full_unstemmed | A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing |
title_short | A Sampling-Based Unfixed Orientation Search Method for Dual Manipulator Cooperative Manufacturing |
title_sort | sampling-based unfixed orientation search method for dual manipulator cooperative manufacturing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9003517/ https://www.ncbi.nlm.nih.gov/pubmed/35408116 http://dx.doi.org/10.3390/s22072502 |
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