Robust Lidar Based Localization Scheme for Unmanned Ground Vehicle via Multisensor Fusion.
This article proposes a robust and precise localization scheme for unmanned ground vehicle (UGV) in global positioning system (GPS) denied and GPS challenged environments via multisensor fusion approach. The localization scheme is proposed to be under an available point cloud map. First, initialization in localization module is designed to calculate the initial position of UGV in map using the Gaussian projection approach and obtain the frame transformation between the 3 D lidar and the inertial measurement unit (IMU) Second, the best alignment between each scan frame and the available submap is obtained, and the pose of vehicle relative to the origin of map is calculated. Third, the precise pose of UGV is well predicted by integrating the data from 3 D lidar and IMU. Fourth, in order to visually verify the proposed localization scheme, the motion of vehicle is visualized by designing the visualization module. Note that the preprocessing module aims to process the raw scan data. The availability of our proposed localization scheme is verified by conducting experiments in our campus.
IEEE transactions on neural networks and learning systems