无人机无地图巡检输电塔绝缘子，定位误差小于0.16米。
Autonomous Inspection of Power Line Insulators with UAV on an Unmapped Transmission Tower
- 融合相机与激光雷达，实时检测并定位绝缘子。
- 单次飞行可节省24%巡检时间，实测定位误差仅0.16米。
- 适合电力巡检自动化，尤其适用于未知环境的无人作业。
本文提出一种在线巡检算法，使无人机在无先验地图的情况下自主绕输电塔飞行并获取详细检测图像。算法基于相机-激光雷达传感器融合，利用卷积神经网络检测绝缘子，将激光点云投影至图像并用边界框过滤。检测流程结合了基于DBSCAN、RANSAC和PCA的多种绝缘子定位方法。通过仿真与真实飞行验证了算法性能：仿真中，单次飞行策略相比传统双飞行策略可节省最多24%巡检时间；真实实验中，最优方法的绝缘子平均水平与垂直定位误差分别为0.16±0.08米和0.16±0.11米，相较于最相关方法，水平定位误差方差降低一个数量级以上。
原文摘要 · Abstract (English)
This paper introduces an online inspection algorithm that enables an autonomous UAV to fly around a transmission tower and obtain detailed inspection images without a prior map of the tower. Our algorithm relies on camera-LiDAR sensor fusion for online detection and localization of insulators. In particular, the algorithm is based on insulator detection using a convolutional neural network, projection of LiDAR points onto the image, and filtering them using the bounding boxes. The detection pipeline is coupled with several proposed insulator localization methods based on DBSCAN, RANSAC, and PCA algorithms. The performance of the proposed online inspection algorithm and camera-LiDAR sensor fusion pipeline is demonstrated through simulation and real-world flights. In simulation, we showed that our single-flight inspection strategy can save up to 24 % of total inspection time, compared to the two-flight strategy of scanning the tower and afterwards visiting the inspection waypoints in the optimal way. In a real-world experiment, the best performing proposed method achieves a mean horizontal and vertical localization error for the insulator of 0.16 +- 0.08 m and 0.16 +- 0.11 m, respectively. Compared to the most relevant approach, the proposed method achieves more than an order of magnitude lower variance in horizontal insulator localization error.
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