A Real-Time and Multi-Sensor-Based Landing Area Recognition System for UAVs

  1. Liu, Fei
  2. Shan, Jiayao
  3. Xiong, Binyu
  4. Fang, Zheng
  5. González Aguilera, Diego 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Revista:
Drones

ISSN: 2504-446X

Ano de publicación: 2022

Volume: 6

Número: 5

Páxinas: 118

Tipo: Artigo

DOI: 10.3390/DRONES6050118 GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: Drones

Resumo

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.

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