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

Yongfeng Li, Pingan Peng (), Huan Li, Jinghua Xie, Liangbin Liu and Jing Xiao
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Yongfeng Li: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Pingan Peng: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Huan Li: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Jinghua Xie: Light Alloy Research Institute, Central South University, Changsha 410083, China
Liangbin Liu: School of Electrical Engineering, Hunan Industry Polytechnic, Changsha 410208, China
Jing Xiao: School of Electrical Engineering, Hunan Industry Polytechnic, Changsha 410208, China

Sustainability, 2023, vol. 15, issue 12, 1-19

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

Keywords: rock-drilling jumbo; optimal path planning; 3D scanning; TSP (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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