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...

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Main Authors: Huanwei Wang, Shangjie Lou, Jing Jing, Yisen Wang, Wei Liu, Tieming Liu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853577/?tool=EBI
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author Huanwei Wang
Shangjie Lou
Jing Jing
Yisen Wang
Wei Liu
Tieming Liu
author_facet Huanwei Wang
Shangjie Lou
Jing Jing
Yisen Wang
Wei Liu
Tieming Liu
author_sort Huanwei Wang
collection DOAJ
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%.
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spelling doaj.art-580a8b95222d444dbca4b247ae8a72382022-12-21T17:24:10ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01172The EBS-A* algorithm: An improved A* algorithm for path planningHuanwei WangShangjie LouJing JingYisen WangWei LiuTieming LiuPath 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%.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853577/?tool=EBI
spellingShingle Huanwei Wang
Shangjie Lou
Jing Jing
Yisen Wang
Wei Liu
Tieming Liu
The EBS-A* algorithm: An improved A* algorithm for path planning
PLoS ONE
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
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853577/?tool=EBI
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