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+).

中文翻译：

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使用基于视觉的导航对无人机进行无线充电

为了更有效地进行空中监视，在相应距离处设置充电板，以便无人驾驶飞行器（UAV）可以在不着陆的情况下维持其运行。通常需要人工干预才能使无人机着陆进行充电并延长其任务。为了使无人机能够自主运行，提出了使用电感耦合进行无线充电。使用这种方法，无人机的电池会被充电，直到它到达下一个充电站。本文重点关注该过程的两个重要方面：用于充电板检测的基于视觉的导航和无线充电。设计了线圈，并使用 Ansys 和 Maxwell 软件分析了其他参数，如互感、耦合系数和线圈之间的有效电力传输距离。建造了四轴飞行器，电池和激光雷达传感器连接到 Arduino 控制器，分别用于低电池电压检测和高度测量。每当电池电压低时，无人机就会使用全球定位导航系统转向最近的充电台。为了测试这个过程，四轴飞行器使用图像处理器 (Raspberry Pi B+) 中预定义的基于视觉的算法飞过充电板。