Tight Integration of INS/Stereo VO/Digital Map for Land Vehicle Navigation

Abstract

This paper proposes a method for tight integration of IMU (Inertial Measurement Unit), stereo <small>VO</small> (Visual Odometry) and digital map for land vehicle navigation, which effectively limits the quick drift of <small>DR</small> (Dead Reckoning) navigation system. In this method, the <small>INS</small> provides the dynamic information of the land vehicle, which is used to predict the position and attitude of cameras in order to obtain the predicted pixel coordinates of features on the image. The difference between the measured and predicted pixel coordinates is used to reduce the accumulated errors of <small>INS</small>. To implement the proposed method, an Extended Kalman filter (<small>EKF</small>) is first used to integrate the inertial and visual sensor data. The integrated solution of position, velocity and azimuth is then applied by fuzzy logic map matching (<small>MM</small>) to project the vehicle location on the correct road link. The projected position on the road link and the road link azimuth can finally be used to reduce the dead reckoning drifts. In this way, the accumulated system errors can be significantly reduced. The testing results indicate that the horizontal <small>RMSE</small> (root-mean-square-error) of the proposed method is less than 20 meters over a traveled distance of five kilometers and the relative horizontal error is below 0.4 percent.