Slope inspection under dense vegetation using LiDAR-based quadrotors

Wenyi Liu, Yunfan Ren, Rui Guo, Vickie W. W. Kong, Anthony S. P. Hung, Fangcheng Zhu, Yixi Cai, Huajie Wu, Yuying Zou and Fu Zhang ()
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Wenyi Liu: The University of Hong Kong
Yunfan Ren: The University of Hong Kong
Rui Guo: The University of Hong Kong
Vickie W. W. Kong: The Government of Hong Kong SAR
Anthony S. P. Hung: The Government of Hong Kong SAR
Fangcheng Zhu: The University of Hong Kong
Yixi Cai: The University of Hong Kong
Huajie Wu: The University of Hong Kong
Yuying Zou: The University of Hong Kong
Fu Zhang: The University of Hong Kong

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract Landslides pose significant threats to residents’ safety and daily lives. To mitigate such risks, flexible debris-resisting barriers are constructed and regularly inspected, a task known as slope inspection. Traditional manual inspections are costly and difficult due to steep terrains and dense vegetation. Unmanned aerial vehicle (UAV) equipped with LiDAR and cameras offers high mobility, making them well-suited for slope inspections. However, existing UAV solutions lack comprehensive frameworks to handle dense vegetation, including robust localization, high-precision mapping, small and dynamic obstacle avoidance, and cluttered under-canopy navigation. To address these challenges, we develop a LiDAR-based quadrotor with a comprehensive software system. Our quadrotor features assisted obstacle avoidance, enabling it to autonomously avoid intricate obstacles while executing pilot commands. Field experiments conducted in collaboration with the Hong Kong Civil Engineering and Development Department demonstrate our quadrotor’s ability to avoid small obstacles and maneuver in dense vegetation, validating its practical potential for slope inspection.

Date: 2025
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DOI: 10.1038/s41467-025-62801-y

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