Drilling Path Planning of Rock-Drilling Jumbo Using a Vehicle-Mounted 3D Scanner

Achieving intelligent rock excavation is an important development direction in underground engineering construction. Currently, some rock-drilling jumbos are able to perform autonomous operations under ideal contour surfaces. However, irregular surfaces resulting from factors such as characteristics, drilling deviation, and blasting effects present a significant challenge for automated non-ideal surfaces, which constrains the intelligentization of excavation. To address this issue, paper proposes method extracting planning paths based on vehicle-mounted 3D scanner. This effectively extracts optimizes paths, thereby improving work efficiency safety. Specifically, proposed includes: (i) real-time scanning cross-sectional contours using scanner construct accurate three-dimensional point-cloud model obtain over-digging information; acquired data compared with theoretical maps vehicle’s coordinate system re-plan blasting-hole point set; (ii) volume-based dynamic search algorithm irregularities detect potential collisions between holes; (iii) conversion sequence new hole set into traveling salesman problem (TSP), optimization Hybrid Greedy Genetic Algorithm (HGGA) achieve path traversal all positions. The effectiveness was verified certain mine example. results show that overall recognition rate reached over 80%, number arm significantly reduced, distance traveled by rig reduced 35% improved genetic algorithm-based planning.