Home Journals Articles Updates About
CN
image
收藏切换
Q-Learning Based Dual Drone Coverage Path Planning
收藏切换
PDF
Jiayu CHEN1, Wen LI1, Tairong LI2, Zhiru LI1, Ziyi WANG1, Pengyun CHEN1
Journal of Telemetry, Tracking and Command | 2025, 46(4) : 96 - 104
Less
收藏切换
Journal of Telemetry, Tracking and Command | 2025, 46(4): 96-104
• TT & C Communication and Navigation •
Q-Learning Based Dual Drone Coverage Path Planning
Full
Jiayu CHEN1, Wen LI1, Tairong LI2, Zhiru LI1, Ziyi WANG1, Pengyun CHEN1
Affiliations
  • 1.North University of China, Taiyuan 030000, China
  • 2.Jinan Green City Development Investment Group Co., Ltd, Jinan 250000, China
Published: 2025-07-15 doi: 10.12347/j.ycyk.20241022001
Outline
收藏切换

The objective of coverage path planning is to ensure that Unmanned Aerial Vehicles (UAVs) achieve complete coverage of the target area. Previous studies assigned UAVs the task of covering each sub-area separately. However, this study proposes a new methodology in which two UAVs collaborate across the entire search area, achieving coverage tasks more flexibly while enhancing efficiency. This paper aims to address the high cost of traditional UAV coverage path planning by proposing a dual-UAVcoverage path planning algorithm based on Q-Learning. To reduce the time taken for the process, a grid-based rotating area partitioning algorithm is used to minimize the search area. The path planning is transformed into a multi-objective function optimisation problem, and the Double-Q-Learning algorithm balances global search and local exploitation, iteratively optimising the path with a total cost function that considers distance and turning costs. The simulation results demonstrate that the proposed algorithm can achieve complete coverage of different target areas with a lower total cost.

Coverage path planning  /  Dual unmanned aerial vehicles  /  Double-Q-Learning  /  Collaborative control  /  Rotating area  /  Multi-Objective function
Jiayu CHEN, Wen LI, Tairong LI, Zhiru LI, Ziyi WANG, Pengyun CHEN. Q-Learning Based Dual Drone Coverage Path Planning[J]. Journal of Telemetry, Tracking and Command, 2025 , 46 (4) : 96 -104 . DOI: 10.12347/j.ycyk.20241022001
Appendix
Less
Year 2025 volume 46 Issue 4
PDF
86
35
Cite this Article
BibTeX
Article Info
doi: 10.12347/j.ycyk.20241022001
  • Receive Date：2024-10-22
  • Online Date：2026-03-13
  • Published：2025-07-15
Article Data
Affiliations
History
  • Received：2024-10-22
  • Revised：2025-03-08
Funding
Affiliations
    1.North University of China, Taiyuan 030000, China
    2.Jinan Green City Development Investment Group Co., Ltd, Jinan 250000, China
References
Share
https://castjournals.cast.org.cn/joweb/ycyk/EN/10.12347/j.ycyk.20241022001
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House