iMag+: An Accurate and Rapidly Deployable Inertial Magneto-Inductive SLAM System

Bo Wei, Niki Trigoni, Andrew Markham

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
37 Downloads (Pure)

Abstract

Localisation is an important part of many applications. Our motivating scenarios are short-term construction work and emergency rescue. These scenarios also require rapid setup and robustness to environmental conditions additional to localisation accuracy. These requirements preclude the use of many traditional high-performance methods, e.g. vision-based, laser-based, Ultra-wide band (UWB) and Global Positioning System (GPS)-based localisation systems. To overcome these challenges, we introduce iMag+, an accurate and rapidly deployable inertial magneto-inductive (MI) mapping and localisation system, which only requires monitored workers to carry a single MI transmitter and an inertial measurement unit in order to localise themselves with minimal setup effort. However, one major challenge is to use distorted and ambiguous MI location estimates for localisation. To solve this challenge, we propose a novel method to use MI devices for sensing environmental distortions for accurate closing inertial loops. We also suggest a robust and efficient first quadrant estimator to sanitise the ambiguous MI estimates. By applying robust simultaneous localisation and mapping (SLAM), our proposed localisation method achieves excellent tracking accuracy and can improve performance significantly compared with only using a Magneto-inductive device or inertial measurement unit (IMU) for localisation.
Original languageEnglish
Pages (from-to)3644-3655
Number of pages12
JournalIEEE Transactions on Mobile Computing
Volume21
Issue number10
Early online date4 Mar 2021
DOIs
Publication statusPublished - 1 Oct 2022

Keywords

  • Distortion
  • Distortion measurement
  • Global Positioning System
  • Inertial measurements
  • Localisation
  • Magnetic resonance imaging
  • Magneto-inductive device
  • Radio transmitters
  • SLAM
  • Simultaneous localization and mapping
  • Trajectory

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