eU2U: Energy-efficient Wireless Charging and Trajectory Design for IoT Data Collection

Abstract

Thanks to their high maneuverability, high flexibility, and low cost, unmanned aerial vehicles (UAVs) have been widely used for data collection in the Internet of Things (IoT). To deal with UAV's onboard battery limitation, UAV-to-UAV (U2U) wireless charging mechanism emerges as a promising solution for extending flight distance and reducing mission completion time. However, U2U charging mechanisms encounter key challenges of limited wireless charging distance and energy loss. In this paper, we propose eU2U, a novel energy-efficient wireless charging and trajectory design approach for IoT data collection. We develop eU2U based on the distributed laser charging (DLC) system for its compact size and meter-level wireless power transmission. To minimize the total energy consumption, we build holistic power and energy consumption models for U2U-enabled data collection. With joint considerations on the wireless charging energy loss and delay constraint, we propose a heuristic algorithm to derive the most energy-efficient locations of the U2U charging points and the UAV trajectories, where the charging points are determined from the Fermat point and the battery drain point. Extensive evaluations show that eU2U can reduce the total energy consumption by 44.52% as compared to state-of-the-art schemes.