Research on detection method of airborne obstacle avoidance lidar

Xianzhe Wang; Xiaodong Jia; Kui Zhou; Hao Zhang; Tao Zhou

doi:10.1117/12.3007725

18 December 2023 Research on detection method of airborne obstacle avoidance lidar

Xianzhe Wang, Xiaodong Jia, Kui Zhou, Hao Zhang, Tao Zhou

Proceedings Volume 12963, AOPC 2023: Optical Sensing, Imaging, and Display Technology and Applications; and Biomedical Optics; 1296318 (2023) https://doi.org/10.1117/12.3007725
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China

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.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xianzhe Wang, Xiaodong Jia, Kui Zhou, Hao Zhang, and Tao Zhou "Research on detection method of airborne obstacle avoidance lidar", Proc. SPIE 12963, AOPC 2023: Optical Sensing, Imaging, and Display Technology and Applications; and Biomedical Optics, 1296318 (18 December 2023); https://doi.org/10.1117/12.3007725

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