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

Author

Listed:
  • Yongfeng Li

    (School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
    School of Electrical Engineering, Hunan Industry Polytechnic, Changsha 410208, 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)

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.

Suggested Citation

  • Yongfeng Li & Pingan Peng & Huan Li & Jinghua Xie & Liangbin Liu & Jing Xiao, 2023. "Drilling Path Planning of Rock-Drilling Jumbo Using a Vehicle-Mounted 3D Scanner," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9737-:d:1173926
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    References listed on IDEAS

    as
    1. Da’ad Ahmad Albalawneh & Mohamad Afendee Mohamed & Amandeep Kaur, 2022. "Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-20, September.
    2. Adam Wróblewski & Jacek Wodecki & Paweł Trybała & Radosław Zimroz, 2022. "A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data," Energies, MDPI, vol. 15(17), pages 1-20, August.
    3. Jakub Janus & Piotr Ostrogórski, 2022. "Underground Mine Tunnel Modelling Using Laser Scan Data in Relation to Manual Geometry Measurements," Energies, MDPI, vol. 15(7), pages 1-15, March.
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