Two Particle Filter-Based INS/LiDAR-Integrated Mobile Robot Localization

Abstract

In order to achieve high precision localization, this paper presents an integrated localization scheme employs two particle filters (PFs) for fusing the inertial navigation systems (INS)-based and the light detection and ranging (LiDAR)-based data. A novel data fusion model is designed, which considers the robot position error, velocity error, and the orientation error. Meanwhile, two-PFs based data fusion filer is designed. The position errors measured by the two-PFs in real tests is 0.059 m. The experimental results verify the effectiveness of two-PFs method proposed in reducing the mobile robot’s position error compared with the two-EKF method.