Review on common algorithms in path panning and improvements

Xinyi Li

doi:10.54254/2755-2721/6/20230732

Research Article

Open access

Published on 14 June 2023

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Li,X. (2023). Review on common algorithms in path panning and improvements. Applied and Computational Engineering,6,6-10.

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Review on common algorithms in path panning and improvements

Xinyi Li *^,1,

¹ Department of Physics and Astronomy, University College London, Gower Street, London, England, WC1E 6BT

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/6/20230732

Abstract

Based on the cooperation of artificial intelligence (AI) and unmanned driving technology, finding the best path from the starting node to the target node in the shortest time is a research hotspot. The required path planning algorithms can therefore be classified according to their different approaches to solving the problem. This paper focuses on Dijkstra’s algorithm, A* algorithm, Ant colony optimization, and genetic algorithm. It also discusses the present problems of these algorithms and some improvements made by researchers focusing on automated guided vehicle path planning.

Keywords

AVG, Path planning, A* algorithm, Ant colony optimisation, Genetic algorithm.

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References

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[2]. Liang B., Yang XM., (2020). Study on a Path Planning Method Based on the Improved Dijkstra Algorithm, Informatization Research, 46(2), pp. 13-16, http://www.cqvip.com/qk/91231a/202002/7102460649.html.

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Cite this article

Li,X. (2023). Review on common algorithms in path panning and improvements. Applied and Computational Engineering,6,6-10.

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 3rd International Conference on Signal Processing and Machine Learning

Conference website: http://www.confspml.org

ISBN：978-1-915371-59-1(Print) / 978-1-915371-60-7(Online)

Conference date: 25 February 2023

Editor：Omer Burak Istanbullu

Series: Applied and Computational Engineering

Volume number: Vol.6

ISSN：2755-2721(Print) / 2755-273X(Online)

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