Research on autonomous navigation and automatic control technology of roadway cleaning robot

This paper addresses three key challenges faced by coal mine roadway cleaning robots operating in long straight underground roadways without satellite signals: localization degradation, difficulty in multi-process coordination, and labor-intensive attachment replacement. An integrated technical framework combining autonomous navigation, hierarchical collaborative control, and automatic attachment replacement is proposed. For autonomous navigation, an angle-clustering ground segmentation method is combined with a tightly coupled unscented Kalman filter (UKF) for fusion positioning, effectively suppressing axial drift. Furthermore, an attitudeaware improved A* global planning algorithm is developed to eliminate the need for terminal orientation adjustment. For collaborative control, a hierarchical finite state machine based architecture is constructed to enable autonomous multi-process scheduling. For attachment replacement, a distance-triggered coarsetofine segmented heterogeneous perception fusion strategy is introduced. This strategy continuously weights and fuses joint state feedback with visual positioning information, achieving full-process automatic attachment replacement. Underground industrial trials, with a cumulative operation of 160 hours and a total footage of 60 meters, show that the average trajectory error is 0.01 m, the terminal heading deviation is 3.8°, and the dynamic obstacle avoidance success rate is 92%. The overall process success rate reaches 80%, and the manipulator end-effector tracking error is 0.12 m. Fourteen out of fifteen?attachment replacements were successful, with an average cycle time of 4.8 min per replacement, representing a 60% efficiency improvement over manual-assisted methods. The number of operators per shift is reduced from 5 to 2 (a 60% reduction), while per-capita efficiency increases from 1.8 m3/shift to 2.6 m3/shift. The proposed framework effectively resolves the three core challenges-positioning degradation, multi-process coordination, and automatic attachment replacement-for roadway cleaning robots in unstructured confined underground environments, significantly enhancing both operational safety and overall efficiency.