Abstract:

Unmanned Aerial Vehicle（UAV） will become the main tool for future power inspections. At present, its flight path is mainly designed based on GPS. Low GPS positioning accuracy and weak GPS signals in some areas are the main bottlenecks preventing the widespread application of UAV power inspection. Aiming at the situation awareness of transmission lines in complex environments, an UAV autonomous inspection system based on monocular vision is proposed to realize autonomous navigation without GPS. The system identifies and detects the target based on deep learning and uses the projection relationship of monocular vision to perform three-dimensional positioning on a detection target with a known size. Then, the drone flight control program based on the DJI SDK is used to adjust the drone’s flight attitude and autonomously navigate to achieve real-time inspection by the drone. The experimental results show that the positioning errors of the system in the three directions of the world coordinate system [X,][Y] and [Z] are 0.31 m, 0.06 m, and 0.24 m, and the processing speed is 0.76 frames per second when it is 10 meters away from the target. The accuracy and feasibility have been verified.

Key words: UAV inspection, monocular vision, object detection, DJI SDK, real-time positioning

摘要：

无人机（UAV）将成为未来电力巡检的主要工具，目前其飞行路径主要根据GPS进行设计。GPS定位精度低，部分区域GPS信号弱，是阻碍无人机电力巡检广泛应用的主要瓶颈。针对复杂环境下的输电线路态势感知，提出一种基于单目视觉的无人机自主巡检系统，实现脱离GPS的自主导航。该系统采用基于深度学习的目标识别检测算法，利用单目视觉的投影变换对尺度已知的待检测目标进行三维定位，然后通过基于大疆SDK开发的飞控程序调整无人机的飞行姿态并自主导航，实现无人机实时巡检。实验结果表明，距离目标物10?m时，该系统在世界坐标系[X、][Y、][Z]三个方向的定位误差分别为0.31 m、0.06 m、0.24 m，处理速度0.76 frame/s，准确性和可行性得到了验证。

关键词: 无人机巡检, 单目视觉, 目标检测, 大疆SDK, 实时定位