Wireless power charging of drone using vision-based navigation

For more efficient aerial surveillance, charging pads are set up at corresponding distances so that an unmanned aerial vehicle (UAV) can sustain its operations without landing. Usually manual intervention is required to land a UAV for charging and so extend its mission. To enable a UAV to operate autonomously, wireless power charging using inductive coupling is proposed. Using this method, the UAV's battery is charged until it reaches the next charging station. This paper focuses on two significant aspects of the process: vision-based navigation for charging pad detection, and wireless power charging. The coils were designed, and other parameters like mutual inductance, coupling coefficient and the distance between the coils for effective power transmission were analysed, using Ansys and Maxwell software. A quadcopter was built, with battery and Lidar sensor connected to the Arduino controller for low battery voltage detection and height measurement, respectively. Whenever the battery voltage is low, the UAV is steered towards the nearest charging pad using the global position navigation system. To test the process, the quadcopter was flown over the charging pad using a vision-based algorithm pre-defined in the image processor (Raspberry Pi B+).