文章摘要
引用本文:张超,王芳,李楠.基于视觉的惯性导航误差在线修正[J].导航定位与授时,2018,5(3):104-110 本文二维码信息
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基于视觉的惯性导航误差在线修正
The Online Correction of IMU Biases for Visual-Inertial Navigation
  
DOI:
中文关键词:  IMU零偏估计  李群和李代数  预积分  Kalman滤波
English Keywords:Estimation of IMU biases  Lie group and Lie algebra  Preintegration  Kalman filter
基金项目:
作者单位
张超 航天科工智能机器人有限责任公司北京 100074 
王芳 航天科工智能机器人有限责任公司北京 100074 
李楠 航天科工智能机器人有限责任公司北京 100074 
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中文摘要:
      陀螺零偏和加速度计零偏是影响惯性测量单元(IMU)积分精度的重要因素。提供一组精确的实时的零偏估计可以提高IMU的积分精度,为视觉导航提供良好的位姿预测,提高整个系统的动态性能。通过合理地建立IMU的噪声模型以及IMU和视觉的组合方程,利用一种基于李群和李代数知识的IMU预积分方法将零偏进行合理的线性化,运用Kalman滤波进行IMU零偏的在线估计。实验结果表明,通过本文的修正方法,惯性导航的平均积累误差由0.034m/s提高到0.0037m/s,精度明显提高。
English Summary:
      The IMU(Inertial Measurement Unit, here refers to gyroscopes and accelerometers) biases are the major factors affecting the accuracy of inertial navigation system. Accurate real-time estimation of IMU biases can improve the integration accuracy of IMU, better predict the position and attitude for camera and improve the dynamic performance of the navigation system. The noise model of IMU and visual-inertial combined models are properly developed. The equations of IMU biases are linearized through preintegrating IMU measurements based on Lie group and Lie algebra, and IMU biases are estimated by using the Kalman filter. The experimental results show that the accuracy of inertial navigation system is improved obviously. The average accumulation error of inertial navigation system is increased from 0.034m/s to 0.0037m/s, and the accuracy is improved obviously.
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