Sensors Utilisation and Data Collection of Underground Mining
Access Status
Open access
Date
2022Supervisor
David Belton
Petra Helmholz
David McMeekin
Type
Thesis
Award
MPhil
Metadata
Show full item recordFaculty
Science and Engineering
School
School of Earth and Planetary Sciences
Collection
Abstract
This study reviews IMU significance and performance for underground mine drone localisation. This research has designed a Kalman filter which extracts reliable information from raw data. Kalman filter for INS combines different measurements considering estimated errors to produce a trajectory including time, position and attitude. To evaluate the feasibility of the proposed method, a prototype has been designed and evaluated. Experimental results indicate that the designed Kalman filter estimates the internal states of a system.