Author: Ma, Wanfeng; Zhang, Yong; Zhao, Qinjun; Liu, Tongqian
Title: Two Particle Filter-Based INS/LiDAR-Integrated Mobile Robot Localization Cord-id: frm0ffh2 Document date: 2020_6_8
ID: frm0ffh2
Snippet: 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. T
Document: 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.
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