Abstract
Automatic positioning technology of underground vehicles has become the key technology for the intelligent development of coal mines. To improve the comprehensive positioning accuracy of unmanned automatic vehicles in coal mines, an 18-D model of an odometer-aided inertial navigation system (INS) and a positioning model of an extended Kalman filter-based ultra-wideband (UWB) are established based on the vehicle kinematics equation. A tight integrated state estimation model is proposed to restrain the long-time drift of the INS and enhance the instability of the UWB system. A local positioning reference system based on an infrared motion capture system is established for the first time. Experimental tests show that the average positioning error of the proposed algorithm is 6.03 cm in the forward direction, and the root-mean-square error increased by 36.09% and 38.24% compared with those of the INS and UWB system, respectively. It is experimentally verified that the integrated positioning system achieves decimeter-level positioning accuracy in a coal mine roadway environment.
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