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一种单目视觉ORB-SLAM/INS组合导航方法 被引量:34

Integrated navigation method of monocular ORB-SLAM/INS
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摘要 针对惯性/卫星组合导航系统在卫星导航失效时无法使用的问题,提出了单目视觉ORB-SLAM/INS组合导航方法,用于扩展组合导航系统在强干扰环境和室内环境的应用范围。该算法分为两个阶段:初始化阶段,当ORB-SLAM形成闭环时设计算法在线估计单目视觉ORB-SLAM算法的尺度因子;导航阶段,ORB-SLAM系统输出的位置信息经过尺度变换后作为观测量进行卡尔曼滤波,估计INS导航系统的误差状态量从而修正惯导系统的误差。设计了硬件和软件平台对提出的组合导航方法进行试验验证。跑车实验结果表明:所设计的ORB-SLAM/INS组合导航系统具有较高的定位精度,导航时间6 min定位误差为1.162 m,且不随时间漂移,具有很强的应用价值。 In order to solve such problem that an integrated INS/GNSS navigation system stops working in satellite failure situation, a deeply-integrated navigation method of monocular ORB-SLAM/INS is proposed to extend the application range of the integrated navigation system in severe interference environment and indoor circumstances. The method can be divided into two phases: in initialization phase, an algorithm is designed to estimate the scale factor online when the ORB-SLAM forms a closed loop; in navigation phase, the error of INS is corrected after the error states of INS are estimated through a Kalman filter whose observations is ORB-SLAM positions. The hardware and software platforms are designed to test the proposed integrated navigation method. Field test results indicate that the position accuracy of the integrated navigation system is satisfactory, with 1.162 m mean error in 6 min and no drift with time, showing that the proposed method has a notable application value.
出处 《中国惯性技术学报》 EI CSCD 北大核心 2016年第5期633-637,共5页 Journal of Chinese Inertial Technology
基金 国家自然科学基金(61004002)
关键词 ORB-SLAM INS 尺度因子 卡尔曼滤波 组合导航 ORB-SLAM INS scale factor Kalman filter integrated navigation
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  • 1万德钧;房建成.惯性导航初始对准[M]南京:东南大学出版社,1998.
  • 2Baziw J,Leondes C T. In-flight alignment and calibration of inertial measurement units-Part 1:General formulation[J].IEEE Transactions on Aerospace and Electronic Systems,1972,(04):439-449.
  • 3Baziw J,Leondes C T. In-flight alignment and calibration of inertial measurement units-Part II:Experimental results[J].IEEE Transactions on Aerospace and Electronic Systems,1972,(04):450-465.
  • 4Mirzaei F M,Roumeliotis S I. A Kalman filter-based algorithm for IMU-camera calibration:Observability analysis and performance evaluation[J].IEEE TRANSACTIONS ON ROBOTICS,2008,(05):1143-1156.
  • 5Li M,Mourikis A I. High-precision,consistent EKF-based visual-inertial odometry[J].The International Journal of Robotics Research,2013,(06):690-711.
  • 6Fang Q,Huang X. UKF for integrated vision and inertial navigation based on three-view geometry[J].IEEE SENSORS JOURNAL,2013,(07):2711-2719.
  • 7Li R,Liu J,Zhang L,et al.LIDAR/MEMS IMU integrated navigation(SLAM)method for a small UAV in indoor environments[C]//2014 IEEE International Symposium on Inertial Sensors and Systems.2014:1-15.
  • 8Shen L,Li D,Luo F.A study on laser speckle correlation method applied in triangulation displacement measurement[J].Optik-International Journal for Light and Electron Optics,2013,124(20):4544-4548.
  • 9Konolige K,Augenbraun J,Donaldson N,et al.A low-cost laser distance sensor[C]//2008 IEEE International Conference on Robotics and Automation.2008:3002-3008.
  • 10Schmalz C,Forster F,Schick A,et al.An endoscopic 3D scanner based on structured light[J].Medical image analysis,2012,16(5):1063-1072.

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