Abstract
In this letter, a novel-feature-based simultaneous localization and mapping (SLAM) approach based on detection of magnetic beacons is presented as a convenient and accurate navigation solution. The magnetic beacons can be accurately detected with unknown background magnetic field by modeling the background field with polynomials and performing joint estimation. By taking the beacons as landmarks, a particle-filter-based SLAM model is established with the dead-reckoning system as state prediction and the relative positions of magnetic beacons as measurement. The potential false detection results are excluded to improve the robustness of the system and reduce computation cost. Experiments based on real-world data are performed to validate the effectiveness and accuracy of the approach.
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