无人机自主降落标识检测方法若干研究进展

doi:10.7527/S1000-6893.2021.25882

Abstract

Abstract: To further promote the research and development on sea/land-air cross-domain collaborative technology in China, the main research achievements and the latest progresses of autonomous landing marker detection methods for the Unmanned Aerial Vehicle (UAV) are reviewed. Firstly, following the introduction of vision guided UAV autonomous landing, the marker detection methods based on image segmentation, classifier and deep learning are discussed. Secondly, the overseas and domestic research teams and achievements of autonomous landing of UAV on static and moving platforms such as vehicles and ships are introduced. Landing markers and detection methods used by the teams are summarized. Finally, a number of key technical issues and feasible solutions for further investigations are discussed in terms of marker detection on moving platforms and in complex environments, system software algorithms, hardware equipment and multi-sensor fusion. How to overcome the dependence on artificial marker and use deep learning ideas for detection of safe landing areas in non-cooperative environments in the future are also discussed.

Key words: cross-domain collaboration, UAV, autonomous landing, marker detection, deep learning

CLC Number:

V279
TJ85

ZHAO Liangyu, LI Dan, ZHAO Chenyue, JIANG Fei. Some achievements on detection methods of UAV autonomous landing markers[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 25882-025882.

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Some achievements on detection methods of UAV autonomous landing markers

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