Research on detection method of airborne obstacle avoidance lidar

Abstract

Complicated environment and obstacles like power lines are pernicious to low-flying helicopters. A novel obstacle detection algorithm for onboard LiDAR evadible system is proposed, which lowers false alarm rate (FAR) and raises detection speed (DS). Firstly, the pass-through filter and planarization voxel filter are used for denoising and sampling reduction. Then, the point cloud is separated by adaptive threshold elevation filtering. Finally, the power lines are extracted with line feature constraint. Experimental results show the maximum detection distance for power lines is up to 800 m, recall rate, over 95%, false alarm rate, below 5%, and that the detection time is less than 100 ms.