Saying goodbyes to rotating your phone: Magnetometer calibration during SLAM

While Wi-Fi positioning is still more common indoors, using magnetic field features has become widely known and utilized as an alternative or supporting source of information. Magnetometer bias presents significant challenge in magnetic field navigation and SLAM. Traditionally, magnetometers have be...

Full description

Saved in:
Bibliographic Details
Main Authors: Vallivaara, Ilari, Dong, Yinhuan, Arslan, Tughrul
Format: Conference Proceeding
Language:English
Subjects:
Calibration
indoor positioning
magnetometer
Magnetometers
Manuals
mobile robotics
Particle filters
Reliability
Robots
Shape
Simultaneous localization and mapping
SLAM
Wireless fidelity
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:While Wi-Fi positioning is still more common indoors, using magnetic field features has become widely known and utilized as an alternative or supporting source of information. Magnetometer bias presents significant challenge in magnetic field navigation and SLAM. Traditionally, magnetometers have been calibrated using standard sphere or ellipsoid fitting methods and by requiring manual user procedures, such as rotating a smartphone in a figure-eight shape. This is not always feasible, particularly when the magnetometer is attached to heavy or fast-moving platforms, or when user behavior cannot be reliably controlled. Recent research has proposed using map data for calibration during positioning. This paper takes a step further and verifies that a pre-collected map is not needed; instead, calibration can be done as part of a SLAM process. The presented solution uses a factorized particle filter that factors out calibration in addition to the magnetic field map. The method is validated using smartphone data from a shopping mall and mobile robotics data from an office environment. Results support the claim that magnetometer calibration can be achieved during SLAM with comparable accuracy to manual calibration. Furthermore, the method seems to slightly improve manual calibration when used on top of it, suggesting potential for integrating various calibration approaches.
ISSN:2471-917X
DOI:10.1109/IPIN62893.2024.10786161