A Real-Time and Multi-Sensor-Based Landing Area Recognition System for UAVs
- Liu, Fei
- Shan, Jiayao
- Xiong, Binyu
- Fang, Zheng
- González Aguilera, Diego 1
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1
Universidad de Salamanca
info
ISSN: 2504-446X
Año de publicación: 2022
Volumen: 6
Número: 5
Páginas: 118
Tipo: Artículo
Otras publicaciones en: Drones
Resumen
This paper presents a real-time and multi-sensor-based landing area recognition system for UAVs, which aims to enable UAVs to land safely on open and flat terrain and is suitable for comprehensive unmanned autonomous operation. The landing area recognition system for UAVs is built on the combination of a camera and a 3D LiDAR. The problem is how to fuse the image and point cloud information and realize the landing area recognition to guide the UAV landing autonomously and safely. To solve this problem, firstly, we use a deep learning method to realize the landing area recognition and tracking from images. After that, we project 3D LiDAR point cloud data into camera coordinates to obtain the semantic label of each point. Finally, we use the 3D LiDAR point cloud data with the semantic label to build the 3D environment map and calculate the most suitable area for UAV landing. Experiments show that the proposed method can achieve accurate and robust recognition of landing area for UAVs.
Información de financiación
Financiadores
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National Natural Science Foundation of China
- 62073066, U20A20197
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Science and Technology on Near-Surface Detection Laboratory
- 6142414200208
- No.2019JH1/10100026
- N2226001
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Aeronautical Science Foundation of China
- No. 201941050001
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