煤矿巷道清理机器人自主导航与协同控制OA

To address localization degradation of coal mine roadway cleaning robots in long,straight roadways where satellite signals are unavailable,difficulties in multi-process coordination,and reliance on manual intervention for attachment replacement,a comprehensive control method integrating autonomous navigation,multi-tool collaborative control,and automatic attachment replacement of fixture is proposed.For autonomous navigation,a fusion localization method combining angle-clustering-based ground segmentation with the Unscented Kalman Filter(UKF)was employed to suppress axial drift,and an improved pose-aware A* global planning algorithm was designed to eliminate the need for final pose adjustment.For collaborative control,a layered architecture based on a hierarchical finite-state machine was constructed to enable autonomous scheduling of multiple processes.For attachment replacement,a distance-triggered heterogeneous perception fusion strategy with coarse-to-fine staging was proposed;joint-state feedback and visual localization information were continuously weighted and fused to complete the entire attachment replacement process autonomously.An underground industrial test involving a cumulative operating time of 160 h and an advance of 60 m was conducted.Results showed that the coal mine roadway cleaning robot had a mean trajectory error of 0.01 m,a final heading deviation of 3.8°,and a dynamic obstacle avoidance success rate of 92％.The full-process success rate was 80％,and the manipulator end-effector tracking error was 0.12 m.The success rate of automatic attachment replacement was 93.3％,and the mean duration per replacement was 4.8 min.The number of operators per shift was reduced from 5 to 2,a reduction of 60％,while per-capita efficiency increased from 1.8 m3/shift to 2.6 m3/shift.