基于机器视觉的植保无人机自主着陆技术研究  

Research on Autonomous Landing Technology of Spraying Drone Based on Machine Vision

作　　者：于坤林[1] 谢志明[1] 刘肩山 YU Kunlin;XIE Zhiming;LIU Jianshan(Changsha Aeronautical Vocational and Technical College,Changsha 410124,China)

机构地区：[1]长沙航空职业技术学院,湖南长沙410124

出　　处：《现代信息科技》2021年第11期48-51,共4页Modern Information Technology

基　　金：2018年度湖南省自然科学基金科教联合基金项目“基于机器视觉的农业植保无人机仿地自主飞行技术研究”(2018JJ5061)。

摘　　要：鉴于机器视觉导航方式具有安全可靠,导航精度高等优点,文章提出一种基于机器视觉的植保无人机自主着陆算法,并对该算法进行了研究:采用自动阈值的Canny算子对着陆地面图标进行边缘检测和目标识别,采用亚像素级Harris角点检测算法对着陆地面标志图像进行特征提取和特征匹配,根据特征点匹配估计出无人机相对着陆点地面标志的三维位姿。并采用仿真软件对算法进行了对比实验,验证了所用算法的有效性和准确性。In view of the advantages of safe,reliable and high navigation accuracy of machine vision navigation mode,an autonomous landing algorithm of spraying drone based on machine vision is proposed and studied in this paper:Canny operator with automatic threshold is used for edge detection and target recognition of landing ground icons,the sub-pixel Harris corner detection algorithm is used to extract and match the features of the landing ground sign images,and the three-dimensional pose of the spraying drone relative to the ground sign of the landing point is estimated according to the feature point matching.The simulation software is used to compare the algorithms,and the effectiveness and accuracy of the used algorithms are verified.

关 键 词：机器视觉 植保无人机 着陆标志识别 位姿估计 自主着陆 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]