上海交通大学学报

上海交通大学学报（自然版） ›› 2015, Vol. 49 ›› Issue (09): 1387-1393.

• 航空、航天 • 上一篇    下一篇

无人飞行器双目视觉位姿估计算法改进与验证

张梁1，徐锦法1，夏青元2，于永军1   

  1. (1. 南京航空航天大学 直升机旋翼动力学国家级重点实验室， 南京 210016；2. 南京理工大学 高维信息智能感知与系统教育部重点实验室， 南京 210094)
  • 收稿日期:2014-08-28
  • 基金资助:

    装备预研基金项目(B2520110008),江苏高校优势学科建设工程项目,高维信息智能感知与系统教育部重点实验室（南京理工大学）基金（30920140122006）,中国博士后科学基金(2013M541668)资助

An Improvement and Verification of Position/Attitude Estimation Algorithm Based on Binocular Vision for Unmanned Aerial Vehicle

ZHANG Liang1,XU Jinfa1,XIA Qingyuan2,YU Yongjun1   

  1. (1. National Key Laboratory of Rotorcraft Aeromechanics, Nanjing University of Aeronautics and  Astronautics, Nanjing 210016, China;2. Key Laboratory of Intelligent Perception and Systems for HighDimensional Information of the Ministry of Education, Nanjing University of Science and Technology, Nanjing 210094, China)
  • Received:2014-08-28

摘要：

摘要：  针对无人飞行器（UAV）在未知复杂环境下的导航问题，提出一种基于双目视觉的UAV位置和姿态估计算法.利用基于非线性尺度空间的KAZE特征构建立体图像对的特征点检测与描述，用Knn算法进行特征点匹配，导出相机坐标系下特征点三维坐标，用随机抽样一致（RANSAC）算法与LM迭代算法获得UAV姿态和位置估计值.实验验证结果表明，基于KAZE特征的UAV双目视觉位姿估计算法的准确性、实时性与可重复性好，能满足UAV实时导航要求.
关键词：  无人飞行器； 双目视觉； 位姿估计
中图分类号：  V 249.31文献标志码：  A

Abstract:

Abstract： Aimed at the problem of navigation of unmanned aerial vehicle(UAV) in a complex unknown environment, an algorithm of position and attitude estimation based on binocular vision was described and improved in this paper. The feature points in the stereo image pairs were detected and described using the KAZE features in the nonlinear scale space. The feature points were matched with the Knn algorithm. The 3D stereo information of the feature points was calculated in the camera coordinate system. The position and attitude of UAV were estimated with the RANSAC algorithm and the LM iteration algorithm. Some experiments were conducted. The result shows that KAZE features have better accuracy, realtime and repeatability than those of SIFT and SURF. The improved algorithm can meet the requirements of UAV realtime navigation.
Key words：

Key words: unmanned aerial vehicle (UAV), binocular vision, position/attitude estimation