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Open AccessArticle
Adaptive Aberrance Repressed Correlation Filters with Cooperative Optimization in High-Dimensional Unmanned Aerial Vehicle Task Allocation and Trajectory Planning
by
Zijie Zheng
Zijie Zheng 1,*
,
Zhijun Zhang
Zhijun Zhang 1,
Zhenzhang Li
Zhenzhang Li 2
,
Qiuda Yu
Qiuda Yu 1
and
Ya Jiang
Ya Jiang 1
1
School of Automation Science and Engineering, South China University of Technology, Guangzhou 510006, China
2
School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China
*
Author to whom correspondence should be addressed.
Electronics 2024, 13(15), 3071; https://doi.org/10.3390/electronics13153071 (registering DOI)
Submission received: 29 May 2024
/
Revised: 20 July 2024
/
Accepted: 30 July 2024
/
Published: 2 August 2024
Abstract
In the rapidly evolving field of unmanned aerial vehicle (UAV) applications, the complexity of task planning and trajectory optimization, particularly in high-dimensional operational environments, is increasingly challenging. This study addresses these challenges by developing the Adaptive Distortion Suppression Correlation Filter Cooperative Optimization (ARCF-ICO) algorithm, designed for high-dimensional UAV task allocation and trajectory planning. The ARCF-ICO algorithm combines advanced correlation filter technologies with multi-objective optimization techniques, enhancing the precision of trajectory planning and efficiency of task allocation. By incorporating weather conditions and other environmental factors, the algorithm ensures robust performance at low altitudes. The ARCF-ICO algorithm improves UAV tracking stability and accuracy by suppressing distortions, facilitating optimal path selection and task execution. Experimental validation using the UAV123@10fps and OTB-100 datasets demonstrates that the ARCF-ICO algorithm outperforms existing methods in Area Under the Curve (AUC) and Precision metrics. Additionally, the algorithm’s consideration of battery consumption and endurance further validates its applicability to current UAV technologies. This research advances UAV mission planning and sets new standards for UAV deployment in both civilian and military applications, where adaptability and accuracy are critical.
Share and Cite
MDPI and ACS Style
Zheng, Z.; Zhang, Z.; Li, Z.; Yu, Q.; Jiang, Y.
Adaptive Aberrance Repressed Correlation Filters with Cooperative Optimization in High-Dimensional Unmanned Aerial Vehicle Task Allocation and Trajectory Planning. Electronics 2024, 13, 3071.
https://doi.org/10.3390/electronics13153071
AMA Style
Zheng Z, Zhang Z, Li Z, Yu Q, Jiang Y.
Adaptive Aberrance Repressed Correlation Filters with Cooperative Optimization in High-Dimensional Unmanned Aerial Vehicle Task Allocation and Trajectory Planning. Electronics. 2024; 13(15):3071.
https://doi.org/10.3390/electronics13153071
Chicago/Turabian Style
Zheng, Zijie, Zhijun Zhang, Zhenzhang Li, Qiuda Yu, and Ya Jiang.
2024. "Adaptive Aberrance Repressed Correlation Filters with Cooperative Optimization in High-Dimensional Unmanned Aerial Vehicle Task Allocation and Trajectory Planning" Electronics 13, no. 15: 3071.
https://doi.org/10.3390/electronics13153071
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