Indoor SLAM using a foot-mounted IMU and the local magnetic field

Conference paper (2022)

Authors

M.E.A. Osman Team Manon Kok - Mechanical, Maritime and Materials Engineering
F.M. Viset Team Manon Kok - Mechanical, Maritime and Materials Engineering
M. Kok Team Manon Kok - Mechanical, Maritime and Materials Engineering
Research Group
Team Manon Kok (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 M.E.A. Osman, F.M. Viset, M. Kok
DOI
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https://doi.org/10.23919/FUSION49751.2022.9841252
SLAM Indoor localization Inertial sensors , magnetic field anomalies Rao-Blackwellized particle filter
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Manon Kok

Abstract

In this paper, a simultaneous localization and mapping algorithm for tracking the motion of a pedestrian with a foot-mounted inertial measurement unit is proposed. The algorithm uses two maps, namely, a motion map and a magnetic field map. The motion map captures typical motion patterns of pedestrians in buildings that are constrained by e.g. corridors and doors. The magnetic map models local magnetic field anomalies in the environment using a Gaussian process model and uses them as position information. These maps are used in a Rao-Blackwellized particle filter to correct the pedestrian position and orientation estimates from the pedestrian dead-reckoning. The pedestrian dead-reckoning is computed using an extended Kalman filter with zero-velocity updates. The algorithm is validated using experimental sequences and the results show the efficacy of the algorithm in localizing pedestrians in indoor environments.