Energy-Efficient Trajectory Planning for Smart Sensing in IoT Networks Using Quadrotor UAVs.

Quadrotor unmanned aerial vehicles (UAVs) are widely used as flexible and mobile access points and information carriers for the future Internet of Things (IoT). This work studies a quadrotor UAV-assisted IoT network, where the UAV helps to collect sensing data from a group of IoT users. Our goal is to optimize the UAV's overall energy consumption required to complete the sensing task. Firstly, we propose a more accurate and mathematically tractable model to characterize the UAV's real-time energy consumption, which accounts for the UAV's dynamics, brushless direct current (BLDC) motor dynamics and aerodynamics. Then, we can show that the UAV's circular flight based on the proposed energy-consumption model consumes less energy than that of hover flight. Therefore, a fly-circle-communicate (FCC) trajectory design algorithm, adopting Dubins curves for circular flight, is proposed and derived to save energy and increase flight duration. Employing the FCC strategy, the UAV moves to each IoT user and implements a circular flight in the sequence solved by the travelling-salesman-problem (TSP) algorithm. Finally, we evaluate the efficiency of the proposed algorithm in a mobile sensing network by comparing the proposed algorithm with the conventional hover-communicate (HC) algorithm in terms of energy consumption. Numerical results show that the FCC algorithm reduces energy consumption by 1-10% compared to the HC algorithm, and also improves the UAV's flight duration and the sensing network's service range.