Indoor Mobile Robot Localization Using Ambient Magnetic Fields and Range Measurements

In this paper we present a method for solving an indoor SLAM and relocation problem using ambient magnetic fields and radio sources. Specifically, we exploit the magnetic field anomalies and noisy radio ranges in indoor environments. A robot with two magnetometers and one active radio range sensor first explores the unknown environment based on the simultaneous localization and mapping (SLAM) technique, gathering its path and some useful multisensory observations. The gathered data are then applied to the Monte Carlo localization (MCL)-based relocation algorithms. The performance of the proposed methods is validated by simulation using the real-world data.