期刊文献+

基于对偶四元数的单目视觉/惯性组合导航算法 被引量:1

Algorithm for monocular camera/SINS integrated navigation based-on dual quaternion
下载PDF
导出
摘要 提出一种适用于结构化道路的单目视觉/惯性组合导航定位算法。针对点特征匹配和连续多帧追踪受车速和相机视野制约的不足,提取道路上车道线的直线特征,引入对偶四元数描述直线特征。在基于对偶四元数的相对位姿估计算法的基础上,推导了图像特征增量与相机位姿增量的表达式。通过配准和时间同步,用惯导系统和相机分别解算的载体速度之差作为组合导航的观测量,建立kalman滤波修正组合导航系统的误差,包括相机测速标度因数误差。车载实验结果表明在结构化道路上算法是有效的。 An algorithm of monocular camera/SINS integrated navigation is presented for structural road. In order to overcome the difficulties of point features matching and tracking, which are restricted by carrier velocity and camera view, line features are extracted from the lane marks on the road. The line features are represented by dual quatemion. Compared with the relative pose estimation algorithm based on dual quaternion, the proposed algorithm deduced the formula of image feature increment and camera position increment. After registration and time synchronization, the velocity computation difference between the SINS and the camera was chosen as observation of integrated navigation. A Kalman filter was used to correct the integrated navigation error including the camera scale factor error of velocity measurement. The experiment results show that the proposed algorithm is accurate for structural road.
出处 《国防科技大学学报》 EI CAS CSCD 北大核心 2012年第3期80-84,共5页 Journal of National University of Defense Technology
基金 高等学校博士学科点专项科研基金资助项目(20069998009) 教育部新世纪优秀人才支持计划(NCET-07-0225)
关键词 结构化道路 单目视觉 SINS 对偶四元数 组合导航 structural road monocular camera SINS dual quatemion integrated navigation
  • 相关文献

参考文献3

二级参考文献27

  • 1张庆君,胡修林,叶斌,钟山.基于双目视觉的航天器间相对位置和姿态的测量方法[J].宇航学报,2008,29(1):156-161. 被引量:44
  • 2张世杰,曹喜滨,李晖.交会对接航天器间相对位姿参数单目视觉测量的解析算法[J].光学技术,2005,31(1):6-10. 被引量:15
  • 3江刚武,龚辉,王净,姜挺.空间飞行器交会对接相对位置和姿态的在轨自检校光学成像测量算法[J].宇航学报,2007,28(1):15-21. 被引量:11
  • 4Fintzel K, Bendahan R, Vestri C, etal. 3D Parking assistant system[A]. Proceedings of the IEEE Intelligent Vehicles Symposium[C]. Piscataway, NJ, USA: IEEE, 2004. 881-886.
  • 5Wybo S, Bendahan R, Bougnoux S, et al. Movement detection for safer backward maneuvers[A]. Proceedings of the IEEE Intelligent Vehicles Symposium[C]. Piscataway, NJ, USA: IEEE, 2006. 453-459.
  • 6Yamaguchi K, Kato T, Ninomiya Y. Moving obstacle detection using monocular vision[A]. Proceedings of the IEEE Intelligent Vehicles Symposium[C]. Piscataway, NJ, USA: IEEE, 2006. 288-293.
  • 7Suzuki T, Kanade T. Measurement of vehicle motion and orientation using optical flow[A]. Proceedings of the IEEE Conference on Intelligent Transportation Systems[C]. Piscataway, NJ, USA: IEEE, 1999. 25-30.
  • 8Hartiey R, Zisserman A. Multiple View Geometry in Computer Vision[M]. Cambridge, UK: Cambridge University Press, 2004.
  • 9Stein G, Mano O, Shashua A. A robust method for computing vehicle ego-motion[A]. Proceedings of the IEEE Intelligent Vehicles Symposium[C]. Piscataway, NJ, USA: IEEE, 2000. 362-368.
  • 10Scharer S, Baltes J, Anderson J. Practical ego-motion estimation for mobile robots[A]. Proceedings of the IEEE Conference on Robotics, Automation and Mechatronics[C]. Piscataway, NJ, USA: IEEE, 2004. 921-926.

共引文献40

同被引文献12

引证文献1

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部