A Real-Time Trajectory Estimation Algorithm for the Virtual Side of an AGV Digital Twin Based on UKF

XinYue Zhang; XiYin Liang

doi:10.63313/FE.9004

Authors

XinYue Zhang College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, GanSu, 730070, China Author
XiYin Liang College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, GanSu, 730070, China Author

DOI:

https://doi.org/10.63313/FE.9004

Keywords:

AGV digital twin, trajectory estimation, unscented Kalman filter (UKF), intermittent measurements, station-based correction

Abstract

To address the insufficient trajectory estimation accuracy of the virtual side in AGV digital twins under intermittent measurements, a real-time trajectory estimation algorithm that integrates the Unscented Kalman Filter (UKF) with periodic station-based correction is proposed. Nonlinear state and measurement equations adapted to AGV motion characteristics are constructed. The UKF is employed to realize real-time position recursion based on intermittent velocity and heading information, while high-precision position information from fixed stations is used to correct accumulated errors. Simulation results demonstrate that the proposed algorithm can effectively suppress error accumulation and achieve accurate tracking of the physical trajectory by the virtual side, providing technical support for precise trajectory replication in AGV digital twin systems.

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