Trajectory planning method based on multi-objective ant colony algorithm for forming section of roadway

被引:0
|
作者
Guo Y. [1 ,2 ]
Huang Y. [1 ]
Gong D. [2 ]
Xia H. [2 ]
机构
[1] School of Mechanical Electronic and Information Engineering, China University of Mining and Technology-Beijing, Beijing
[2] School of Information and Control Engineering, China University of Mining and Technology, Xuzhou
来源
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2022年 / 50卷 / 05期
关键词
Energy-consumption of excavating; Improved multi-objective ant colony algorithm; Multi-objective optimization; Trajectory planning; Under-excavation area;
D O I
10.13245/j.hust.220520
中图分类号
学科分类号
摘要
Aiming at the problem that the single optimized objective was normally taken and the distribution of coal and rock was ignored in existing trajectory planning methods for forming section of a roadway, a multi-objective trajectory planning model was built by taking the coal and rock distribution of roadway section and the characteristics of tunneling equipment as constraints, in which the best forming quality and the lowest energy-consumption of excavating were comprehensive considered, and an improved multi-objective ant colony algorithm was proposed to solve the problem. In the proposed algorithm, to avoid low search efficiency and high infeasibility caused by random initialized trajectory, the prior knowledge of paths was extracted and the imbalanced assigning strategy of the initial pheromone was designed, and an adaptive adjustment strategy for the objective importance coefficient was proposed to prevent the search from falling into local optimal and search stagnation. Considering the complexity of the gangue distribution in actual roadway sections, four simulation environments of roadway sections were constructed to verify the sensitivity of parameter and the effectiveness of the proposed strategies. Results show that compared with the other four algorithms, the proposed algorithm has better convergence and distribution, and the optimal trajectory can be obtained in the trajectory planning for forming section of a roadway. © 2022, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
引用
收藏
页码:115 / 122
页数:7
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