Research Article
Open Access
A High-Efficiency Two-Layer Path Planning Method for UAVs in Vast Airspace
1
School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
* Corresponding Author:
Fengbao Yang,
[email protected]
Volume 1, Issue 2
2024
Received: 29 July 2024
Accepted: 23 September 2024
Published: 27 September 2024
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CC BY 4.0 License
Article Information
Published in
Chinese Journal of Information Fusion
Volume/Issue
Volume 1, Issue 2, 2024
Pages
109-125
Cited by
4 (Crossref)
3 (Scopus)
Abstract
Facing the challenges of low efficiency and poor quality in UAV 3D path planning within large-scale airspace complex environments, this paper introduces a divide-and-conquer approach, proposing a dual-layer path planning method based on multi-source information fusion. The method decomposes traditional path planning into two steps: heading planning and trajectory planning, ensuring both planning efficiency and path quality. This method segregates the solution process into two distinct stages: heading planning and path planning, thereby ensuring the planning of both efficiency and path quality. Firstly, the path planning phase is formulated as a multi-objective optimization problem, taking into account the environmental constraints of the UAV mission and path safety. A heading planning layer is then designed, which incorporates multiple information sources and represents the multidimensional airspace environmental data through an adaptive 2D probabilistic map via information fusion. An improved ant colony algorithm is proposed to efficiently generate high-quality sets of headings, facilitating the preliminary heading planning for UAVs. Then, the three-dimensional environment of the heading regions is extracted, and an improved Dung Beetle algorithm with multiple strategies is proposed to optimize the three-dimensional path in the secondary layer accurately. The efficacy and quality of the proposed path planning methodology are substantiated through comprehensive simulation analysis.
Graphical Abstract
Keywords
two-dimensional probabilistic map
information fusion
trajectory planning
optimization algorithm
two-Layer path planning
Data Availability Statement
Data will be made available on request.
Funding
This work was supported by the National Natural Science Foundation of China under Grant 61972363 and Grant 61672472.
Conflicts of Interest
The authors declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
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Cited By (3)
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2026 38th Chinese Control and Decision Conference (CCDC), 2026 .
[CrossRef] -
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2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025 .
[CrossRef] -
Jianquan Zhang, Fangting Huang, Shuqing Zhu, Xiao Xiao. A Resource Allocation Strategy in Internet of Vehicles Based on Multi-Task Federated Learning and Incentive Mechanism.
IEEE Transactions on Intelligent Transportation Systems, 2025 , 26 (10).
[CrossRef]
* Citation data provided by Crossref Cited-by.
Cite This Article
APA Style
Yang, T. & Yang, F. (2024). A High-Efficiency Two-Layer Path Planning Method for UAVs in Vast airspace. Chinese Journal of Information Fusion, 1(2), 109–125. https://doi.org/10.62762/CJIF.2024.596648
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TY - JOUR AU - Yang, Tongyao AU - Yang, Fengbao PY - 2024 DA - 2024/09/27 TI - A High-Efficiency Two-Layer Path Planning Method for UAVs in Vast Airspace JO - Chinese Journal of Information Fusion T2 - Chinese Journal of Information Fusion JF - Chinese Journal of Information Fusion VL - 1 IS - 2 SP - 109 EP - 125 DO - 10.62762/CJIF.2024.596648 UR - https://www.icck.org/article/abs/CJIF.2024.596648 KW - two-dimensional probabilistic map KW - information fusion KW - trajectory planning KW - optimization algorithm KW - two-Layer path planning AB - Facing the challenges of low efficiency and poor quality in UAV 3D path planning within large-scale airspace complex environments, this paper introduces a divide-and-conquer approach, proposing a dual-layer path planning method based on multi-source information fusion. The method decomposes traditional path planning into two steps: heading planning and trajectory planning, ensuring both planning efficiency and path quality. This method segregates the solution process into two distinct stages: heading planning and path planning, thereby ensuring the planning of both efficiency and path quality. Firstly, the path planning phase is formulated as a multi-objective optimization problem, taking into account the environmental constraints of the UAV mission and path safety. A heading planning layer is then designed, which incorporates multiple information sources and represents the multidimensional airspace environmental data through an adaptive 2D probabilistic map via information fusion. An improved ant colony algorithm is proposed to efficiently generate high-quality sets of headings, facilitating the preliminary heading planning for UAVs. Then, the three-dimensional environment of the heading regions is extracted, and an improved Dung Beetle algorithm with multiple strategies is proposed to optimize the three-dimensional path in the secondary layer accurately. The efficacy and quality of the proposed path planning methodology are substantiated through comprehensive simulation analysis. SN - 2998-3371 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Yang2024A,
author = {Tongyao Yang and Fengbao Yang},
title = {A High-Efficiency Two-Layer Path Planning Method for UAVs in Vast Airspace},
journal = {Chinese Journal of Information Fusion},
year = {2024},
volume = {1},
number = {2},
pages = {109-125},
doi = {10.62762/CJIF.2024.596648},
url = {https://www.icck.org/article/abs/CJIF.2024.596648},
abstract = {Facing the challenges of low efficiency and poor quality in UAV 3D path planning within large-scale airspace complex environments, this paper introduces a divide-and-conquer approach, proposing a dual-layer path planning method based on multi-source information fusion. The method decomposes traditional path planning into two steps: heading planning and trajectory planning, ensuring both planning efficiency and path quality. This method segregates the solution process into two distinct stages: heading planning and path planning, thereby ensuring the planning of both efficiency and path quality. Firstly, the path planning phase is formulated as a multi-objective optimization problem, taking into account the environmental constraints of the UAV mission and path safety. A heading planning layer is then designed, which incorporates multiple information sources and represents the multidimensional airspace environmental data through an adaptive 2D probabilistic map via information fusion. An improved ant colony algorithm is proposed to efficiently generate high-quality sets of headings, facilitating the preliminary heading planning for UAVs. Then, the three-dimensional environment of the heading regions is extracted, and an improved Dung Beetle algorithm with multiple strategies is proposed to optimize the three-dimensional path in the secondary layer accurately. The efficacy and quality of the proposed path planning methodology are substantiated through comprehensive simulation analysis.},
keywords = {two-dimensional probabilistic map, information fusion, trajectory planning, optimization algorithm, two-Layer path planning},
issn = {2998-3371},
publisher = {Institute of Central Computation and Knowledge}
}
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Copyright © 2024 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), 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.
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