An Efficient and Robust UAVs' Path Planning Approach for Timely Data Collection in Wireless Sensor Networks

The flexible and controllable mobility makes Unmanned Aerial Vehicle (UAV) useful in collecting data from distributed wireless sensor nodes, especially in emergency situations where infrastructures are destroyed or absent. However, due to the limited battery capacity, the mission duration of UAV is severely restricted, which makes the trajectory design become challenging. In this paper, a data-collection oriented multiple UAVs path planing algorithm is proposed to minimize the data collection time. Specifically, an enhanced particle swarm optimization (E-PSO) algorithm is first proposed to optimize the visiting sequence of sensors, which can shorten the flight time. Moreover, a novel hover-on-edge algorithm is designed by jointly considering wireless communication ranges and locations of sensors in traversal sequence. The proposed algorithms are compatible with UAV flying directly above the sensor (E-PSO) and UAV hovering on the communication range of sensor (HE-PSO) which enhance the robustness of the system. Simulation results demonstrate path distance and flight time reduction of our proposed algorithm.