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Published on 29 March 2024
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Luo,Y. (2024). A fast convergence bidirectional a star path planning algorithm. Applied and Computational Engineering,54,241-247.
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A fast convergence bidirectional a star path planning algorithm

Yixin Luo *,1,
  • 1 Northwest Polytechnic University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/54/20241642

Abstract

A* and bidirectional A* have been classical pathfinding algorithms for long with many derivatives specially designed for their exclusive situations. To solve the problem of the bidirectional A* algorithm being inefficient in some situations, this paper gives a kind of optimized algorithm with a new dynamic parameter in the heuristic function and a 25% increase in efficiency. By modifying the weights, the proportion between distance and efficiency can be well balanced. This paper uses some typical problems for simulation and paints the scatter diagram of different weights to figure out the relationship between the weight and the balance. In the end, the author gives suggestions on optimizing the coefficient due to the rule, which stands for gradually promoting the weight of the dynamic parameter until the path doesn’t keep optimal, for various situations and how to further modify the heuristic function for better performance.

Keywords

Heuristic Algorithm, Path Planning; Bidirectional A* Algorithm, Efficiency Improvement

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Cite this article

Luo,Y. (2024). A fast convergence bidirectional a star path planning algorithm. Applied and Computational Engineering,54,241-247.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 4th International Conference on Signal Processing and Machine Learning

Conference website: https://www.confspml.org/
ISBN:978-1-83558-353-1(Print) / 978-1-83558-354-8(Online)
Conference date: 15 January 2024
Editor:Marwan Omar
Series: Applied and Computational Engineering
Volume number: Vol.54
ISSN:2755-2721(Print) / 2755-273X(Online)

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