An Accurate Underground Autonomous Vehicle Localization System Using RSSI and IMU Data

Positioning autonomous vehicles in an underground mine is essential to improve the safety and efficiency of operations in underground mining. In this paper, we propose a sensor fusion positioning approach by combining data from inertial measurement units (IMU) and from Bluetooth Low Energy (BLE) beacons. Merging information is achieved using the Unscented Kalman Filter (UKF) and the Extended Kalman Filter (EKF). Experiments carried out in an underground mine have demonstrated that using BLE beacons with IMU data yields precise and reliable vehicle location results. The findings underscore the effectiveness of the proposed technique.