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The safety and efficiency of hard rock roadway excavation are the two sides of a coin limiting the implementation of roadway construction. It is an effective way to improve the performance in hard rock tunneling to effectively release the internal stress in rock mass by arranging pre-prepared boreholes in rock section. In order to improve the rock breaking performance and tunneling efficiency, we analyze the borehole positioning accuracy and explore boreholes sequence planning problem in hard rock excavation simulatively and experimentally. The kinematics model of drilling mechanism is established based on the D-H method. RBF neural network algorithm is adopted to accurately position borehole. The results show that accuracy of simulated borehole positioning is controlled at 1.5% while the accuracy is 5.6% of experiment. The Ant Colony Algorithm (ACA) is employed to optimize the sequence planning of drilling boreholes with the optimization goals of minimum moving distance and minimum swing angle separately. Simulation results show that rock-drilling with the minimum swing angle produces smaller positioning deviation and higher efficiency, which is a practical automatic roadway borehole drilling method.

Positioning and Sequence Planning of Drilling Boreholes in Hard Rock Roadway