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 superstrong NdFeBmagnets 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 twodimensional position of an MN is derived from the magnetic dipolemodel. Even a single tri-axismagnetometer 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.

Automated summary

The Magnetic Positioning Approach (MPA) is a reliable solution for Automated Guided Vehicles (AGVs) under fixed route conditions. By simplifying the iterative and optimization algorithms, the MPA based on superstrong NdFeB magnets exhibits superior performance and proposes a simplified MPA scheme based on analytical methods.