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Open AccessArticle

Trajectory Planning for Data Collection of Energy-Constrained Heterogeneous UAVs

College of Communications Engineering, Army Engineering University of PLA, Nanjing 210042, China
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Department of Computer Science and Technology, Nanjing University, Nanjing 210023, China
Author to whom correspondence should be addressed.
Sensors 2019, 19(22), 4884;
Received: 29 September 2019 / Revised: 5 November 2019 / Accepted: 7 November 2019 / Published: 8 November 2019
(This article belongs to the Special Issue Optimization and Communication in UAV Networks)
Nowadays, Unmanned Aerial Vehicles (UAVs) have received growing popularity in the Internet-of-Things (IoT) which often deploys many sensors in a relatively wide region. Since the battery capacity is limited, sensors cannot transmit over a long distance. It is necessary for designing efficient sensor data collection mechanisms to prolong the lifetime of the IoT and enhance data collection efficiency. In this paper, we consider a UAV-enabled data collection scenario, where multiple heterogeneous UAVs with different energy constraints are employed to collect data from sensors. The value of data depends on the importance of the monitoring area of the sensor and the freshness of collected data. Our objective is to maximize the data collection utility by jointly optimizing the communication scheduling and trajectory of each UAV. The data collection utility is determined by the amount and value of the collected data. This problem is a variant of multiple knapsack problem, which is a classical NP-hard problem. First, we transform the initial problem into a submodular function maximization problem under energy constraints, and then we design a novel trajectory planning algorithm to maximize the data collection utility, while accounting for different values of data and different energy constraints of heterogeneous UAVs. Finally, under different network settings, the performance of the proposed trajectory planning algorithm is evaluated via extensive simulations. The results show that the proposed algorithm can obtain maximum data collection utility. View Full-Text
Keywords: unmanned aerial vehicles; trajectory planning; sensors; data collection utility unmanned aerial vehicles; trajectory planning; sensors; data collection utility
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Qin, Z.; Dong, C.; Wang, H.; Li, A.; Dai, H.; Sun, W.; Xu, Z. Trajectory Planning for Data Collection of Energy-Constrained Heterogeneous UAVs. Sensors 2019, 19, 4884.

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