Trajectory Design of Laser-Powered Multi-Drone Enabled Data Collection System for Smart Cities

Du, Yao, Wang, Kezhi, Yang, Kun and Zhang, Guopeng (2019) Trajectory Design of Laser-Powered Multi-Drone Enabled Data Collection System for Smart Cities. In: Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM), December 9 – 13, Waikoloa, Hawaii, USA. IEEE, Piscataway, NJ. ISBN 9781728109633, 9781728109626

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Abstract

This paper considers a multi-drone enabled data collection system for smart cities, where there are two kinds of drones, i.e., Low Altitude Platforms (LAPs) and a High Altitude Platform (HAP). In the proposed system, the LAPs perform data collection tasks for smart cities and the solar-powered HAP provides energy to the LAPs using wireless laser beams. We aim to minimize the total laser charging energy of the HAP, by jointly optimizing the LAPs’ trajectory and the laser charging duration for each LAP, subject to the energy capacity constraints of the LAPs. This problem is formulated as a mixed-integer and non-convex Drones Traveling Problem (DTP), which is a combinatorial optimization problem and NP-hard. We propose an efficient and novel search algorithm named DronesTraveling Algorithm (DTA) to obtain a near-optimal solution. Simulation results show that DTA can deal with the large scale DTP (i.e., more than 400 data collection points) efficiently. Moreover, the DTA only uses 5 iterations to obtain the nearoptimal solution whereas the normal Genetic Algorithm needs nearly 10000 iterations and still fails to obtain an acceptable solution.

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