Research Article
Tightly INS/UWB Combined Indoor AGV Positioning in LOS/NLOS Environment
@INPROCEEDINGS{10.1007/978-3-030-51103-6_30, author={Peisen Li and Shuhui Bi and Tao Shen and Qinjun Zhao}, title={Tightly INS/UWB Combined Indoor AGV Positioning in LOS/NLOS Environment}, proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2020}, month={7}, keywords={Kalman filter (KF) Extending kalman filter (EKF) Tightly-coupled}, doi={10.1007/978-3-030-51103-6_30} }- Peisen Li
Shuhui Bi
Tao Shen
Qinjun Zhao
Year: 2020
Tightly INS/UWB Combined Indoor AGV Positioning in LOS/NLOS Environment
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-030-51103-6_30
Abstract
In view of the defects and shortcomings of traditional Automated Guided Vehicle (AGV) robots in the localization mode and working scene, this paper studies the tightly-coupled integrated localization strategy based on inertial navigation system (INS) with ultra wide band (UWB). This paper presents an interactive multi-model (IMM) to solve the influence of non-line-of-sight (NLOS) on positioning accuracy. In IMM framework, two parallel Kalman filter (KF) models are used to filter the measured distance simultaneously, and then IMM distance is obtained by weighted fusion of two KF filtering results. This paper adopts the tightly-coupled combined method, and performs indoor positioning by extending Kalman filter (EKF). Experiments show that the method can effectively suppress the influence of NLOS error and improve the localization accuracy.
