Reward Maximization for Disaster Zone Monitoring With Heterogeneous UAVs

• Published in: IEEE/ACM transactions on networking Vol. 32; no. 1; pp. 1 - 14
• Main Authors: Xu, Wenzheng, Wang, Chengxi, Xie, Hongbin, Liang, Weifa, Dai, Haipeng, Xu, Zichuan, Wang, Ziming, Guo, Bing, Das, Sajal K.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; approximation algorithm; Autonomous aerial vehicles; Cameras; Disaster area monitoring; Disasters; heterogeneous UAVs; Infrared imagery; Internet of Things; Monitoring; multiple UAV scheduling; Office buildings; orienteering problem; Performance evaluation; Scheduling; School buildings; Sensors; Visualization
• ISSN: 1063-6692; 1558-2566
• DOI: 10.1109/TNET.2023.3300174

In this paper, we study the deployment of <inline-formula> <tex-math notation="LaTeX">K</tex-math> </inline-formula> heterogeneous UAVs to monitor Points of Interest (PoIs) in a disaster zone, where a PoI may represent a school building or an office building, in which people are trapped. A UAV can take images/videos of PoIs and send its collected information back to a nearby rescue station for decision-making. Unlike most existing studies that focused on only homogeneous UAVs, we here study the scheduling of <inline-formula> <tex-math notation="LaTeX">K</tex-math> </inline-formula> heterogeneous UAVs, where different UAVs have different energy capacities and functionalities that lead to different monitoring qualities (monitoring rewards) of each PoI. For example, one type of UAVs can take only visual images while the other type of UAVs can take both visual and thermal infrared images. In this paper, we investigate a problem of scheduling <inline-formula> <tex-math notation="LaTeX">K</tex-math> </inline-formula> heterogeneous UAVs to monitor PoIs so that the sum of monitoring rewards received by all UAVs is maximized, subject to energy capacity on each UAV. We propose the very first <inline-formula> <tex-math notation="LaTeX">\frac{1}{3}</tex-math> </inline-formula>-approximation algorithm for this scheduling problem. We also evaluate the performance of the proposed algorithm, using real parameters of commercial UAVs. Experimental results show that the performance of the proposed algorithm is promising, which is improved by 25%, compared with existing algorithms.