Evidence map›Paper›PMID 42031954›Full record

ArticleScientific reports2026

Task allocation method for anchoring robot with multiple drilling units and multiple tasks in coal mine roadways.

Kexiang Ma, Hongwei Ma, Chuanwei Wang, Siya Sun, Yifeng Guo, Peng Wang, Zhen Nie, Ye Zhang, Hao Su, Xuefei Wu

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Kexiang MaSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Hongwei MaSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Chuanwei WangSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China. 22105016005@stu.xust.edu.cn.
Siya SunSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Yifeng GuoSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Peng WangSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Zhen NieSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Ye ZhangSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Hao SuSchool of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, China.
Xuefei WuCCTEG: Xi'an Research Institute (Group) Co., Ltd, Xi'an, China.

Funding

Natural Science Basic Research Program of Shaanxi Province 2025JC-YBQN-782the Key Research and Development Projects of Shaanxi Province 2023-LL-QY-03the Key Technologies Research and Development Program of China 2023YFC2907600
6 · The paper itself

Abstract

To address the optimal allocation problem of multiple drilling and bolting tasks in a multi-drill anchor robot system for coal mine roadway excavation, a hybrid optimization method (GAVNS) integrating Genetic Algorithm (GA) and Variable Neighborhood Search (VNS) is proposed. Based on roadway geometric parameters and the spatial layout characteristics of multi-drill anchor robots, a layered support process for excavation roadways is developed, dividing the overall support tasks into four independent support layers to achieve layered, parallel, and efficient execution of support tasks. For the optimal configuration of drill quantities in different support layers, a comprehensive optimization model is established considering spatial constraints such as drill working space and feasible operational domains, as well as temporal constraints of support tasks, ensuring efficient operations in each support layer and enabling parallel operation with the excavation robot. Addressing the multi-drill multi-task allocation problem within different support layers, a multi-drill multi-task allocation model is constructed, with a fitness function based on segmented integer encoding and diversified neighborhood structures designed to effectively combine the global search capability of GA with the local optimization advantage of VNS, improving algorithm convergence speed and solution quality. Validation through simulation of coal mine roadway support tasks demonstrates that the proposed GAVNS algorithm outperforms traditional genetic algorithms and single VNS in terms of task completion time, load balancing, and resource utilization. This method has been applied to the coal mine intelligent excavation robot system developed by the team, achieving efficient permanent support operations. It has been in operation for over 10 months in large-section excavation roadways, achieving daily excavation advances exceeding 50 m and monthly advances exceeding 1000 m.

Indexed as

Anchor robotGenetic algorithmMulti-anchor task allocationMultiple drilling unitsStaged roadway support processVariable neighborhood search algorithm

Identifiers

PMID42031954
PMCPMC13276097

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