Research Article
Two Particle Filter-Based INS/LiDAR-Integrated Mobile Robot Localization
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@INPROCEEDINGS{10.1007/978-3-030-51100-5_31, author={Wanfeng Ma and Yong Zhang and Qinjun Zhao and Tongqian Liu}, title={Two Particle Filter-Based INS/LiDAR-Integrated Mobile Robot Localization}, proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part I}, proceedings_a={ICMTEL}, year={2020}, month={7}, keywords={Mobile robot localization INS LiDAR Particle filter}, doi={10.1007/978-3-030-51100-5_31} }- Wanfeng Ma
Yong Zhang
Qinjun Zhao
Tongqian Liu
Year: 2020
Two Particle Filter-Based INS/LiDAR-Integrated Mobile Robot Localization
ICMTEL
Springer
DOI: 10.1007/978-3-030-51100-5_31
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.
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