Online calibration method of lidar positioning based on indoor AGV

Abstract

In the AGV (Automated Guided Vehicle) system, the accuracy of the positioning system often ultimately determines the accuracy of the AGV navigation process and results. Due to the influence of factors such as uneven ground and inertia, the mechanical structure of the lidar will shake during the navigation process, which affects the positioning effect of the forklift. To this end, we adopted an online lidar calibration method, based on the mature EKF (Extended Kalman Filter) algorithm, to estimate the pose and lidar calibration parameters of the AGV in real time. The simulation results show that the method can better estimate the calibration parameters of lidar.