Localization for Autonomous Vehicles Using Environmental Magnetic Field Aided by Magnetic Markers

Vehicle localization is one of the key technical factors for autonomous vehicles. It requires high accuracy, precision, and robustness towards various road conditions. Popular localization methods include global navigation satellite system (GNSS) and visual methods, but their accuracy can degrade in some conditions. This work proposes to use the environmental magnetic field (EMF) for localization to complement the shortcomings of existing methods. EMF is a combination of the Earth's geomagnetic field and magnetic field induced by man-made objects. It has local fluctuations that can be paired with coordinate positions and is time-invariant within a practical timescale. Past works considering its use in road vehicles had problems when applying them to the localization of autonomous vehicles. This work overcomes the problems by creating a two-dimensional magnetic field map using Gaussian process regression, using magnetic markers to enhance EMF fluctuations, and utilizing the Monte Carlo localization (MCL) algorithm. In this work, a 2-D EMF map was generated using measurements from our experiment vehicles. The generated map retained the original magnetic features. Next, the proposed method was validated through simulation and actual vehicle tests using the generated EMF map as a reference. The results showed that the MCL can accurately localize the vehicle and demonstrated the feasibility of the proposed method.