Path tracking of mining boom road-header using SVD-Unscented Kalman Filtering

Abstract

Facing the demand of autonomous path correction of the road-header working underground, a control law was designed and simplified based on the position and orientation deviation model of the road-header against its aimed walking trajectory.Reasonable Lyapunov function is constructed to prove the convergence of the position and orientation deviation that resulted from the designed control law.Based on a certain real time position and orientation detection strategy for the road-header, the possible errors exist during posture adjustments are summarized and classified into two parts: one is the main execution error of the road-header and it is presented by the slip rate of tracks; the other is the main observation error and it is identified as the position and orientation measurement errors.This paper proposed to take advantages of the statistical characteristics of these errors, which is obtained by a certain number of experiments or deductions instead of rigorous theoretical analysis.The SVD-unscented Kalman Filtering is used to modify the commands that are given originally by the controller so as to deduce and reduce the influence of process error and observation error in the process of position and orientation adjusting.The simulation results show that the proposed path tracking control strategy can effectively realize the transition of the road-header to the target roadway in limited adjustment period, and the corresponding recommended speeds of the driving wheels vary continuously and stably in the whole process.The negative influence of process error and observation error is effectively weakened by commands modification based on SVD-unscented Kalman Filtering.The obtained moving trajectory of the road-header coincides with the planned path very well during the adjustment, which is of great repeatability.This proves that the proposed strategy is of great potential to be applied experimentally in underground real road heading scenario.

Keywords

• road-header
• path correction
• position and orientation derivation
• path tracking
• svd- unscented kalman filtering