Joint Task Chain, Power, and UAV Trajectory Optimization Based on an Integrated Multi-UAV System

This paper investigates a task assignment and resource optimization problem in an integrated multi-unmanned aerial vehicle (multi-UAV) system, where multi-UAVs are rationally assigned to complete detection, tracking, and communication tasks. Specifically, we formulate a joint task chain, power, and UAV trajectory optimization problem to maximize the sum of detection, tracking, and communication performance under the constraints of task, UAV, resource, and task web. To address the proposed NP-hard problem, we decompose it into three sub-problems, i.e., the task chain optimization problem, the power optimization problem, and the UAV trajectory optimization problem. We then propose a task chain selection algorithm to more efficiently address the task chain optimization problem by transforming invalid solutions into valid ones. The other two sub-problems are both solved by the successive convex approximation (SCA) algorithm. Based on these three algorithms, an inner-outer iterative optimization (IOIO) algorithm is proposed to iteratively solve the original problem with polynomial time complexity. Simulation results demonstrate that the proposed algorithm achieves better performance compared to other baseline schemes.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-03-24
DOI
https://doi.org/10.1109/tvt.2025.3553874
Citations
6
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
7.66
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article

Joint Task Chain, Power, and UAV Trajectory Optimization Based on an Integrated Multi-UAV System

Kehao Wang, Hyundong Shin, Pei Liu, Xun Zhang et al.
6 citations
IEEE Transactions on Vehicular Technology
Robotic Path Planning Algorithms
7.66
article

Joint Task Chain, Power, and UAV Trajectory Optimization Based on an Integrated Multi-UAV System

Kehao Wang, Hyundong Shin, Pei Liu, Xun Zhang, Xiaobai Li
article en
6 citations

Abstract

This paper investigates a task assignment and resource optimization problem in an integrated multi-unmanned aerial vehicle (multi-UAV) system, where multi-UAVs are rationally assigned to complete detection, tracking, and communication tasks. Specifically, we formulate a joint task chain, power, and UAV trajectory optimization problem to maximize the sum of detection, tracking, and communication performance under the constraints of task, UAV, resource, and task web. To address the proposed NP-hard problem, we decompose it into three sub-problems, i.e., the task chain optimization problem, the power optimization problem, and the UAV trajectory optimization problem. We then propose a task chain selection algorithm to more efficiently address the task chain optimization problem by transforming invalid solutions into valid ones. The other two sub-problems are both solved by the successive convex approximation (SCA) algorithm. Based on these three algorithms, an inner-outer iterative optimization (IOIO) algorithm is proposed to iteratively solve the original problem with polynomial time complexity. Simulation results demonstrate that the proposed algorithm achieves better performance compared to other baseline schemes.

IEEE Transactions on Vehicular TechnologyVol. 74(8)
Wuhan University of Technology (CN), Kyung Hee University (KR)
Affordable and clean energy
Openalex Percentile: Top 3%
Robotic Path Planning Algorithms
7.66
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Joint Task Chain, Power, and UAV Trajectory Optimization Based on an Integrated Multi-UAV System — Kehao Wang, Hyundong Shin, et al. · IEEE Transactions on Vehicular Technology (2025) | TGRS Research Map | TGRS