MagPIE is a publicly available dataset for the evaluation of indoor positioning algorithms that use magnetic anomalies. Our dataset contains IMU and magnetometer measurements along with ground truth position measurements that have centimeter-level accuracy. To produce this dataset, we collected over 13 hours of data (51 kilometers of total distance traveled) from three different buildings, with sensors both handheld and mounted on a wheeled robot, in environments with and without changes in the placement of objects that affect magnetometer measurements ("live loads'').
Dataset and Code
|Building and Platform||Num. Training Cases||Num. Dead Load Cases||Num. Live Load Cases|
|Aggregating over all trials:|
|Total Time||13.96 hrs|
|Total Distance||51.35 km|
|Average Time of Test Cases||90.80 sec|
|Minimum Time of Test Cases||21.10 sec|
|Maximum Time of Test Cases||245.66 sec|
|Average Distance of Test Cases||101.54 m|
|Minimum Distance of Test Cases||23.01 m|
|Maximum Distance of Test Cases||297.98 m|
Related Webpages and Links
D. Hanley, A. B. Faustino, S. D. Zelman, D. A. Degenhardt, and T. Bretl, "MagPIE: A Dataset for Positioning with Magnetic Anomalies", in Eigth International Conference of Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan, September 2017. (accepted) [pdf]
Please send bug reports to David Hanley: firstname.lastname@example.org
7/21/2017 - The relative orientations of the Z Play and Phab 2 Pro for the UGV and WLK cases are different causing issues for mapping based on individual axes measurements. FIXED: README now includes correct rotations matrix for UGV and WLK cases.