3D Trajectory Planning for Real-Time Image Acquisition in UAV-Assisted VR

被引:1
|
作者
Tang, Xiao-Wei [1 ]
Huang, Yi [1 ]
Shi, Yunmei [1 ]
Huang, Xin-Lin [1 ]
Shi, Qingjiang [2 ]
机构
[1] Tongji Univ, Coll Elect & Informat Engn, Shanghai 201804, Peoples R China
[2] Tongji Univ, Coll Software Engn, Shanghai 201804, Peoples R China
关键词
Unmanned aerial vehicles; virtual reality; image acquisition; three-dimensional trajectory design; RESOURCE-ALLOCATION; DESIGN; OPTIMIZATION; MINIMIZATION; NETWORKS; COMMUNICATION; SYSTEM; POWER;
D O I
10.1109/TWC.2023.3274571
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Nowadays, unmanned aerial vehicles (UAVs), empowered with the capability of high-definition image transmission, are used to capture the rapidly changing physical environment by leveraging its high flexibility to reconstruct an immersive realistic virtual environment for metaverse users. In this paper, we consider a novel UAV-assisted image acquisition system where a UAV is dispatched to take off from an initial location to capture real-time images of multiple ground targets and then transfer the captured images back to the ground user for virtual environment reconstruction. We aim to minimize the time for the UAV to complete the image acquisition task by optimizing the three-dimensional UAV trajectory under the constraints of image quality, information causality and energy consumption. To this end, we first formulate the investigated scenario into a mixed integer optimization problem, which, however, is difficult to solve due to the infinite time-varying variables closely coupled with each other. Then, a three-stage progressive algorithm is proposed to obtain an efficient solution to the formulated mixed integer optimization problem, where the constraints of image quality, information causality and energy consumption can be sequentially satisfied. Finally, comprehensive performance evaluation is conducted to verify the effectiveness of the proposed three-stage progressive trajectory design algorithm, and the results show that the proposed algorithm significantly outperforms the benchmark schemes.
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页码:16 / 30
页数:15
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