A Simplified Magnetic Positioning Approach Based on Analytical Method and Data Fusion for Automated Guided Vehicles

Magnetic positioning approach (MPA) is a reliable solution for automated guided vehicles (AGVs) under relatively fixed route conditions. Ferrite magnets are usually buried in the ground and employed as magnetic nails (MNs) for the parking and steering of AGVs. Our previous studies implemented a novel MPA based on super-strong NdFeB magnets and the minimize iterations between magnetometer data and predicted values via the magnetic dipole model, with the advantage of more exceptional positioning performance than traditional MPAs. Nevertheless, the iterative optimization algorithms depend on the initial guess setting; besides, the complicated calculation based on multiple magnetometer data makes it difficult to be executed on a microcontroller in real-time. In this article, we propose a simplified MPA based on the analytical method. The analytical expression for calculating the two-dimensional position of an MN is derived from the magnetic dipole model. Even a single tri-axis magnetometer can localize the MN, whereas multiple magnetometers tend to achieve higher positioning performance. Thus, positioning results of multiple magnetometers are fused based on the confidence criterion. Comparing with the MPA based on the Levenberg–Marquardt algorithm, the proposed MPA could achieve comparable positioning accuracy but with far lower computational complexity and greater robustness. Thereby, this article introduces a new concept of high-precision MPA for AGV applications without the complicated visual perception.