系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (10): 2157-2162.doi: 10.3969/j.issn.1001-506X.2019.10.01

• 电子技术 • 上一篇    下一篇

无人机自主着陆地标实时检测方法

梅立春1, 王彩云2, 赵元富3, 魏文怡2, 李阳雨2   

  1. 1. 南京航空航天大学电子信息工程学院, 江苏 南京 210016;  2. 南京航空航天大学航天学院,江苏 南京 210016;  3. 北京微电子技术研究所, 北京 100076
  • 出版日期:2019-09-25 发布日期:2019-09-24

Real-time detection method of landmark in UAV autonomous landing

MEI Lichun1, WANG Caiyun2, ZHAO Yuanfu3, WEI Wenyi2, LI Yangyu2   

  1. 1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;  2. College of Astronautics, Nanjing University of Aeronautics and Astronautics,Nanjing 210016, China;  3. Beijing Microelectronic Technology Institute, Beijing 100076, China
  • Online:2019-09-25 Published:2019-09-24

摘要: 在基于计算机视觉的无人机自主着陆过程中,地标的设计与检测是关键问题。提出了一种快速轮廓角点检测算法,并设计了一种新型嵌套三角形图案作为无人机自主着陆地标。首先,利用Suzuki-Abe算法提取的背景及目标的整体轮廓信息,进行目标嵌套轮廓提取;其次,通过改进Douglas-Peucker拟合算法来检测轮廓角点。由于优化了角点个数及最远距离两点的寻找方法,在很大程度上减少了计算时间且降低了复杂度。实验结果表明,在距离地标较远、地标部分信息缺失的情况下,该算法准确快速,适合于无人机自主着陆过程位置实时检测。

关键词: 无人机, 自动着陆, 轮廓提取, 角点检测, 地标

Abstract: The design and detection of landmark are key points in the process of unmanned aerial vehicle (UAV) autonomous landing based on computer vision. A fast contour corner detection algorithm is proposed in this paper and a new nested triangle pattern is also designed as a landmark for autonomous landing of UAV. Firstly, the background and target overall contour information, obtained by Suzuki-Abe algorithm, are used to extract the nested contours. Secondly, the corners are detected by the improved Douglas-Peucker fitting algorithm. Due to the optimization of the corners number and the searching method for the farthest two points, the computational time and the complexity are reduced greatly. The experimental results show that the proposed technique performs well when the distance from the landmark is relatively far and the part of landmark information is missing, and it can meet the demand of the real time measurements of the position for the autonomous landing process of UAV.

Key words: unmanned aerial vehicle (UAV), autonomous landing, contour extraction, corner detection, landmark