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Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot

With the development of artificial intelligence, path planning of Autonomous Mobile Robot (AMR) has been a research hotspot in recent years. This paper proposes the improved A* algorithm combined with the greedy algorithm for a multi-objective path planning strategy. Firstly, the evaluation function...

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Detalles Bibliográficos
Autores principales: Xiang, Dan, Lin, Hanxi, Ouyang, Jian, Huang, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345932/
https://www.ncbi.nlm.nih.gov/pubmed/35918508
http://dx.doi.org/10.1038/s41598-022-17684-0
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author Xiang, Dan
Lin, Hanxi
Ouyang, Jian
Huang, Dan
author_facet Xiang, Dan
Lin, Hanxi
Ouyang, Jian
Huang, Dan
author_sort Xiang, Dan
collection PubMed
description With the development of artificial intelligence, path planning of Autonomous Mobile Robot (AMR) has been a research hotspot in recent years. This paper proposes the improved A* algorithm combined with the greedy algorithm for a multi-objective path planning strategy. Firstly, the evaluation function is improved to make the convergence of A* algorithm faster. Secondly, the unnecessary nodes of the A* algorithm are removed, meanwhile only the necessary inflection points are retained for path planning. Thirdly, the improved A* algorithm combined with the greedy algorithm is applied to multi-objective point planning. Finally, path planning is performed for five target nodes in a warehouse environment to compare path lengths, turn angles and other parameters. The simulation results show that the proposed algorithm is smoother and the path length is reduced by about 5%. The results show that the proposed method can reduce a certain path length.
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spelling pubmed-93459322022-08-04 Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot Xiang, Dan Lin, Hanxi Ouyang, Jian Huang, Dan Sci Rep Article With the development of artificial intelligence, path planning of Autonomous Mobile Robot (AMR) has been a research hotspot in recent years. This paper proposes the improved A* algorithm combined with the greedy algorithm for a multi-objective path planning strategy. Firstly, the evaluation function is improved to make the convergence of A* algorithm faster. Secondly, the unnecessary nodes of the A* algorithm are removed, meanwhile only the necessary inflection points are retained for path planning. Thirdly, the improved A* algorithm combined with the greedy algorithm is applied to multi-objective point planning. Finally, path planning is performed for five target nodes in a warehouse environment to compare path lengths, turn angles and other parameters. The simulation results show that the proposed algorithm is smoother and the path length is reduced by about 5%. The results show that the proposed method can reduce a certain path length. Nature Publishing Group UK 2022-08-02 /pmc/articles/PMC9345932/ /pubmed/35918508 http://dx.doi.org/10.1038/s41598-022-17684-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Xiang, Dan
Lin, Hanxi
Ouyang, Jian
Huang, Dan
Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot
title Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot
title_full Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot
title_fullStr Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot
title_full_unstemmed Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot
title_short Combined improved A* and greedy algorithm for path planning of multi-objective mobile robot
title_sort combined improved a* and greedy algorithm for path planning of multi-objective mobile robot
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345932/
https://www.ncbi.nlm.nih.gov/pubmed/35918508
http://dx.doi.org/10.1038/s41598-022-17684-0
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