Abstract:
Recently, Autonomous land vehicle navigation became an important research topic. Most of the land vehicle navigation systems are based on Global Navigation Satellite Syst...Show MoreMetadata
Abstract:
Recently, Autonomous land vehicle navigation became an important research topic. Most of the land vehicle navigation systems are based on Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) integrated system. However, this system doesn't efficiently work in some environments due to the GNSS signal outages and the deterioration of the navigation solution due to the large INS errors. Therefore, INS should be aided to limit its drift during GNSS signal blockage. This research proposes a multi low-cost INS configuration in land vehicle where two low-cost IMU sensors are mounted on the center of rear wheels of the land vehicle to estimate the vehicle's forward velocity through the gyroscopes located in the perpendicular direction of the wheel. A differential wheel odometry based on the Inertial Measurement Unit (IMU) mounted on the rear wheels is proposed to estimate the vehicle's change of heading. The proposed IMU wheel odometers are calibrated by providing GNSS/INS integrated forward velocity and heading change during GNSS signal availability. On the other hand, during GNSS signal outages, the IMU wheel based aiding system provides both velocity and heading change updates to the navigation filter to mitigate the large drift of the on-board IMU.Experimental tests have been implemented and the results show that the Root Mean Square Error (RMSE) of the IMU-based wheel odometer velocity is 0.08 m/sec while the RMSE of the typical odometer velocity obtained from On-Board Diagnostics II (OBD-II) is 0.26 m/sec. On the other hand, the RMSE of the estimated vehicle's heading change by the proposed differential wheel odometry reached 2 degrees/second for 360 second simulated GNSS signal outage. The navigation solution is enhanced when the IMU-based odometer velocity updates the navigation filter Extended Kalman Filter (EKF) and the average position RMSE reaches 4.96 meters, instead of 88.83 meters, for the INS standalone navigation solution during 60 second...
Date of Conference: 18 November 2020 - 16 December 2020
Date Added to IEEE Xplore: 15 February 2021
ISBN Information: