TY - GEN
T1 - iMag: Accurate and Rapidly Deployable Inertial Magneto-Inductive Localisation
AU - Wei, B.
AU - Trigoni, N.
AU - Markham, A.
PY - 2018/5/21
Y1 - 2018/5/21
N2 - Localisation is of importance for many applications. Our motivating scenarios are short-term construction work and emergency rescue. Not only is accuracy necessary, these scenarios also require rapid setup and robustness to environmental conditions. These requirements preclude the use of many traditional methods e.g. vision-based, laser-based, Ultra-wide band (UWB) and Global Positioning System (GPS)-based localisation systems. To solve these challenges, we introduce iMag, an accurate and rapidly deployable inertial magneto-inductive (MI) localisation system. It localises monitored workers using a single MI transmitter and inertial measurement units with minimal setup effort. However, MI location estimates can be distorted and ambiguous. To solve this problem, we suggest a novel method to use MI devices for sensing environmental distortions, and use these to correctly close inertial loops. 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 an inertial measurement unit (IMU) and MI device for localisation.
AB - Localisation is of importance for many applications. Our motivating scenarios are short-term construction work and emergency rescue. Not only is accuracy necessary, these scenarios also require rapid setup and robustness to environmental conditions. These requirements preclude the use of many traditional methods e.g. vision-based, laser-based, Ultra-wide band (UWB) and Global Positioning System (GPS)-based localisation systems. To solve these challenges, we introduce iMag, an accurate and rapidly deployable inertial magneto-inductive (MI) localisation system. It localises monitored workers using a single MI transmitter and inertial measurement units with minimal setup effort. However, MI location estimates can be distorted and ambiguous. To solve this problem, we suggest a novel method to use MI devices for sensing environmental distortions, and use these to correctly close inertial loops. 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 an inertial measurement unit (IMU) and MI device for localisation.
KW - Global Positioning System
KW - sensor placement
KW - SLAM (robots)
KW - wireless sensor networks
KW - inertial magneto-inductive localisation
KW - short-term construction work
KW - iMag
KW - robust simultaneous localisation
KW - inertial measurement units
KW - Transmitters
KW - Robustness
KW - Simultaneous localization and mapping
KW - Magnetic resonance imaging
KW - Distortion
KW - Trajectory
KW - Magneto-inductive device
KW - Inertial measurements
KW - Localisation
KW - SLAM
U2 - 10.1109/ICRA.2018.8460804
DO - 10.1109/ICRA.2018.8460804
M3 - Conference contribution
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 99
EP - 106
BT - 2018 IEEE International Conference on Robotics and Automation (ICRA)
PB - IEEE
ER -