Abstract
The accurate and reliable navigation system is very important for the Unmanned Ground Vehicles (UGVs) in indoor environment, where Global Positioning System (GPS) is almost unreliable or unavailable. This paper leverages the information from gyroscope, wheel encoder and 2D Light Detection and Ranging (LiDAR) in a tightly-coupled integrated navigation system to achieve high navigation accuracy. In this paper, a LiDAR-based line feature extract method is proposed, which is simple to find the different lines, and available in multiple environments. The change of position and orientation estimated by LiDAR line feature matching and INS/odometry is fused by an error-state Extended Kalman Filter (EKF), which can give a periodic correction for the errors accumulation of the inertial sensors. Simulation experiment was carried out and the results prove that the proposed LiDAR-aided integrated navigation system can reduce the error of the position and the accuracy is significantly improved by 74.61%.
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