Positioning of Mine Loaders Based on UWB and IMU

Aiming at the difficulty of precise positioning of load-haul-dump (LHD) machines in complex mine environments, due to the constraints of satellite-denied environments on single positioning technologies and the severe impact of non-line-of-sight (NLOS) conditions, this paper proposes a positioning method suitable for LHD machines in mine environments. This method integrates ultra-wideband (UWB) and inertial measurement unit (IMU) measurement information through an improved error state Kalman filter (ESKF) algorithm. A Dynamic Covariance Robust Method (DCRM) is proposed for ESKF to improve it by constructing a residual covariance matrix and dynamically adjusting the measurement noise covariance matrix through covariance matching technology, achieving adaptive suppression of NLOS error. The experimental results demonstrate that in complex environments, compared to using UWB positioning alone, the improved ESKF positioning algorithm effectively reduces the ultra-wideband positioning error under NLOS conditions by providing prior information of the positioning target. Compared to LS-Taylor, the Extended Kalman Filter algorithm and the Motion Inertia Estimation Adaptive Kalman Filtering, the positioning accuracy is improved by 61%, 50% and 31%, respectively.