Shearer SINS/OD integrated navigation system based on robust closed path calibration

Accurate positioning of shearer is a key technology for completing the straightness detection and improving the level of automation of the fully mechanized mining face. The integrated navigation system of strapdown inertial navigation and odometer based on nonholonomic constraints and closed path calibration is a widely used positioning scheme for shearer. The closed path calibration uses the position information of the previous cutting cycle combined with the displacement distance of support to predict the current position, in order to suppress the error divergence of shearer after multiple cutting cycle. However, there is a large execution error in the hydraulic support displacement process, which seriously interferes with the detection of straightness due to incorrect predicted positions. To solve this problem, a robust closed path calibration method is proposed, which uses the maximum correntropy criterion Kalman filter (MCCKF) instead of the classical KF to reject outliers in the predicted position and improve the robustness; On this basis, the adaptive kernel bandwidth algorithm is introduced into MCCKF to improve the adaptability of the integrated navigation system to complex environments. Experiments have shown that MCCKF can effectively avoid the interference of outliers in predicted positions on straightness detection, and reduce the cumulative error from the first cutting cycle. The MCCKF with adaptive kernel bandwidth can achieve excellent performance without preset parameters.