液晶与显示2018，Vol.33Issue(3)：238-244,7.DOI:10.3788/YJYXS20183303.0238
无人飞行器自主降落区识别方法研究
Method for identifying the landing area of unmanned aerial vehicle
摘要
Abstract
In order to achieve unmanned aerial vehicle self-landing,considering the characteristics of UAVs(unmanned aerial vehicle)landing areas which are lack of features and irregular distribution in different shapes,an UAV landing area identification method is proposed based on point cloud process-ing technologies in this paper.M ulti-view 3D reconstruction algorithm is used to generate point cloud from images captured by a camera fixed on an UAV.Taking the spatial distance as the smoothing term and the height of the points in the Z direction as the similarity term,a 3D point-cloud bilateral filtering algorithm is proposed in this paper to reduce noise points.A cluster segmentation based on the normal and curvature information of point cloud is designed to segment the point clouds.And an improved RANSAC algorithm for plane fitting is used to identify flat areas.Then,a selection method is proposed to select landing area for UAV.At last,several real scenes' images are used to generate point clouds to test the accuracy of the algorithm.The experimental results show that the fluctuation of the identified area is less than 0.125 m@m2,which meet the requirements of UAV's landing.关键词
3D重建/无人飞行器/点云处理Key words
3D reconstruction/unmanned aerial vehicle/point cloud processing分类
信息技术与安全科学引用本文复制引用
黄建宇,屈玉福,姜吉祥..无人飞行器自主降落区识别方法研究[J].液晶与显示,2018,33(3):238-244,7.基金项目
国家自然基金资助项目(No.51675033)Supported by National Natural Science Foundation of China(No.51675033) （No.51675033）
