Optimization of Communication Quality for Energy-Limited Inspection AAV: A Hybrid Algorithm

• Published in: IEEE open journal of the Communications Society Vol. 5; pp. 7900 - 7912
• Main Authors: Wang, Wei, Cao, Jiangling, Yang, Dingcheng, He, Hao, Xu, Zhihai
• Format: Journal Article
• Language: English
• Published: New York IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: AAV inspection system; Algorithms; Autonomous aerial vehicles; Batteries; Communication; Dueling double deep Q network (D3QN); Effectiveness; Energy; Energy consumption; Energy limitation; energy-limited inspection AAV; Flight; Inspection; Optimization; Planning; Rotors; Simulated annealing; simulated annealing (SA); Trajectory; Trajectory optimization; Trajectory planning; Unmanned aerial vehicles; Vectors; Wireless communication
• ISSN: 2644-125X; 2644-125X
• DOI: 10.1109/OJCOMS.2024.3507818

In this paper, we study a autonomous aerial vehicle (AAV) inspection system. In this system, the AAV flies to all inspection points in a certain area for patrol inspection, and the energy of inspection AAV is limited. Our goal is to optimize the communication quality of the AAV by planning the inspection sequence and flight trajectory, so as to ensure that the AAV can complete the inspection task and minimize the outage time subject to limited energy of the AAV. To solve this problem, we propose a hybrid algorithm, which consists of simulated annealing (SA) algorithm and Dueling Double Deep Q Network (D3QN) algorithm. The SA algorithm is used to obtain the inspection sequence of the AAV with the most energy saving. On this basis, the D3QN algorithm is used to optimize the flight trajectory of the energy-limited inspection AAV. To prove the effectiveness of the sub-optimal solution obtained by our proposed algorithm, we use several algorithms as a comparison. Numerical results show that the proposed algorithm is effective in optimizing the communication quality of the inspection AAV with limited energy, and its performance is improved by about 15%-50% compared with other benchmarks.