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

Wei, Bo and Trigoni, Niki and Markham, Andrew (2022) iMag+:An Accurate and Rapidly Deployable Inertial Magneto-Inductive SLAM System. IEEE Transactions on Mobile Computing (TMC), 21 (10). 3644 - 3655.

Full text not available from this repository.


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.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Transactions on Mobile Computing (TMC)
Additional Information:
Author was employed at another UK HEI at the time of submission and was deposited at Northumbria University Repository, see link
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
14 Jun 2022 14:05
Last Modified:
22 Nov 2022 11:33