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The EBS-A* algorithm: An improved A* algorithm for path planning
Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the traditional A* algorithm has some limitations, such as slow planning speed, close to obstacles. In this paper, we propose an improved A*-based algori...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853577/ https://www.ncbi.nlm.nih.gov/pubmed/35176092 http://dx.doi.org/10.1371/journal.pone.0263841 |
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author | Wang, Huanwei Lou, Shangjie Jing, Jing Wang, Yisen Liu, Wei Liu, Tieming |
author_facet | Wang, Huanwei Lou, Shangjie Jing, Jing Wang, Yisen Liu, Wei Liu, Tieming |
author_sort | Wang, Huanwei |
collection | PubMed |
description | Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the traditional A* algorithm has some limitations, such as slow planning speed, close to obstacles. In this paper, we propose an improved A*-based algorithm, called the EBS-A* algorithm, that introduces expansion distance, bidirectional search, and smoothing into path planning. The expansion distance means keeping an extra space from obstacles to improve path reliability by avoiding collisions. Bidirectional search is a strategy searching path from the start node and the goal node simultaneously. Smoothing improves path robustness by reducing the number of right-angle turns. In addition, simulation tests for the EBS-A* algorithm are performed, and the effectiveness of the proposed algorithm is verified by transferring it to a robot operating system (ROS). The experimental results show that compared with the traditional A* algorithm, the proposed algorithm improves the path planning efficiency by 278% and reduces the number of critical nodes by 91.89% and the number of right-angle turns by 100%. |
format | Online Article Text |
id | pubmed-8853577 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-88535772022-02-18 The EBS-A* algorithm: An improved A* algorithm for path planning Wang, Huanwei Lou, Shangjie Jing, Jing Wang, Yisen Liu, Wei Liu, Tieming PLoS One Research Article Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the traditional A* algorithm has some limitations, such as slow planning speed, close to obstacles. In this paper, we propose an improved A*-based algorithm, called the EBS-A* algorithm, that introduces expansion distance, bidirectional search, and smoothing into path planning. The expansion distance means keeping an extra space from obstacles to improve path reliability by avoiding collisions. Bidirectional search is a strategy searching path from the start node and the goal node simultaneously. Smoothing improves path robustness by reducing the number of right-angle turns. In addition, simulation tests for the EBS-A* algorithm are performed, and the effectiveness of the proposed algorithm is verified by transferring it to a robot operating system (ROS). The experimental results show that compared with the traditional A* algorithm, the proposed algorithm improves the path planning efficiency by 278% and reduces the number of critical nodes by 91.89% and the number of right-angle turns by 100%. Public Library of Science 2022-02-17 /pmc/articles/PMC8853577/ /pubmed/35176092 http://dx.doi.org/10.1371/journal.pone.0263841 Text en © 2022 Wang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wang, Huanwei Lou, Shangjie Jing, Jing Wang, Yisen Liu, Wei Liu, Tieming The EBS-A* algorithm: An improved A* algorithm for path planning |
title | The EBS-A* algorithm: An improved A* algorithm for path planning |
title_full | The EBS-A* algorithm: An improved A* algorithm for path planning |
title_fullStr | The EBS-A* algorithm: An improved A* algorithm for path planning |
title_full_unstemmed | The EBS-A* algorithm: An improved A* algorithm for path planning |
title_short | The EBS-A* algorithm: An improved A* algorithm for path planning |
title_sort | ebs-a* algorithm: an improved a* algorithm for path planning |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853577/ https://www.ncbi.nlm.nih.gov/pubmed/35176092 http://dx.doi.org/10.1371/journal.pone.0263841 |
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