The MagPIE2 Dataset for Mapping, Localization, and Simultaneous Localization and Mapping Using Magnetic Fields

This article introduces the Magnetic Positioning Indoor Estimation 2.0 (MagPIE2) dataset, designed to evaluate localization, mapping, and simultaneous localization and mapping (SLAM) methods that rely on the use of magnetic fields. Prior work has shown that contemporary localization methods that use magnetic fields are not robust to height changes that may commonly occur during use by pedestrians and robots. Our dataset contains measurements from magnetometers and inertial measurement units collected inside multiple buildings at multiple heights with both a pedestrian and a ground robot. We used several sensors for ground truth, including visual-inertial SLAM, red-green-blue (RGB) and depth images. We also provide sensor calibration measurements and suggested calibration values. Unlike some previous datasets, MagPIE2 includes trials where ferromagnetic objects (like tables, chairs, and computers) have been moved. This dataset is available for download at https://doi.org/10.13012/B2IDB-0228701_V1.