UAV Data Acquisition and Processing Assisted by UGV-Enabled Mobile Edge Computing

IF 9.9 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Informatics Pub Date : 2025-02-07 DOI:10.1109/TII.2025.3528540
Jianhua Tang;Yao Zeng
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Abstract

Data acquisition and processing (DAP) by uncrewed aerial vehicle (UAV) hold the key to a diverse range of practical applications. However, UAVs often face challenges in completing complex DAP tasks due to inadequate on-board resources. To ameliorate such difficulties, previous researches have explored the mobile edge computing (MEC)-assisted UAV DAP, but they do not prioritize the mobility of MEC servers, resulting in challenges when communication and computation resources are limited. To address this issue, this work proposes a novel design that incorporates a movable uncrewedground vehicle (UGV)-mounted MEC server to assist UAV DAP, which enables the UAV to thoroughly leverage edge resources. Under this design, we aim to maximize UAV DAP ability with constraints including real-time data processing, UGV obstacles avoidance and system motion. Efficient algorithms are proposed, with obstacles avoidance problem solved, from a systematic perspective. Extensive simulation and real-world experiment results demonstrate the effectiveness of our system design and algorithms.
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基于ugv的移动边缘计算辅助无人机数据采集与处理
无人驾驶飞行器(UAV)的数据采集和处理(DAP)是各种实际应用的关键。然而,由于机载资源不足,无人机在完成复杂的DAP任务时经常面临挑战。为了改善这一困难,以往的研究已经探索了移动边缘计算(MEC)辅助无人机DAP,但它们没有优先考虑MEC服务器的移动性,导致在通信和计算资源有限的情况下存在挑战。为了解决这一问题,本工作提出了一种新颖的设计,该设计结合了安装在可移动无人地面车辆(UGV)上的MEC服务器来辅助无人机DAP,从而使无人机能够充分利用边缘资源。在本设计中,我们的目标是在实时数据处理、UGV避障和系统运动等约束下,最大限度地提高无人机的DAP能力。提出了有效的算法,从系统的角度解决了避障问题。大量的仿真和实际实验结果证明了系统设计和算法的有效性。
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来源期刊
IEEE Transactions on Industrial Informatics
IEEE Transactions on Industrial Informatics 工程技术-工程:工业
CiteScore
24.10
自引率
8.90%
发文量
1202
审稿时长
5.1 months
期刊介绍: The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.
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