An Improved NSGA-II-Based Method for Cutting Trajectory Planning of Boom-Type Roadheader
Source abstract
Abstract
This paper proposes a cutting trajectory planning method for boom-type roadheaders using an improved Nondominated Sorting Genetic Algorithm II (NSGA-II) with an elitist strategy. Existing methods often overlook constraints related to cutterhead dimensions and target sections, affecting section formation quality. We develop a kinematic model for coordinate transformations and design a simplified cutterhead and constraint model to generate feasible cutting points. Bi-objective functions—minimizing cutting trajectory length and turning angle—are formulated as a bi-objective traveling salesman problem (BO-TSP) with adjacency constraints. NSGA-II is adapted with enhancements in adjacency constraint handling, population initialization, and genetic operations. Simulations and experiments demonstrate significant improvements in convergence speed and computation time. Virtual cutting experiments confirm trajectory feasibility under varying postures, achieving high formation quality. A comparison of planned and tracked trajectories shows a maximum deviation of 23.879 mm, supporting autonomous cutting control. This method advances cutting trajectory planning for roadway section formation and autonomous roadheader control.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Tunneling and Rock Mechanics · Simulation and Modeling Applications · Industrial Technology and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Shaanxi Key Laboratory of Intelligent Detection and Control for Mining Electromechanical Equipment, Xi’an 710054, China
Faculty of Engineering and Technology, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK
Funding
National Natural Science Foundation of China · Natural Science Foundation of Shaanxi Province · China Postdoctoral Science Foundation · Key R & D project in Shaanxi
References (24)
Show source-provided references
1. Roadheader—A comprehensive review10.1016/j.tust.2019.103148 ↗
2. Challenges and development of the intelligent remote control on roadheaders in coal mine
3. Qu, Y., Ji, X., and Lv, F. (2020). Trajectory Planning for the Cantilevered Road-Header in Path Correction Under the Shaft. Advances in Intelligent Systems and Interactive Applications, Proceedings of the 4th International Conference on Intelligent, Interactive Systems and Applications (IISA2019), Bangkok, Thailand, 28–30 June 2019, Springer.10.1007/978-3-030-34387-3_33 ↗
4. Kinematic models and simulations for trajectory planning in the cutting of spatially-arbitrary cross-sections by a robotic roadheader10.1016/j.tust.2018.03.032 ↗
5. Cutting trajectory planning of sections with complex composition for roadheader10.1177/0954406218768840 ↗
6. Wu, J., Xu, Z., Fang, X., Shi, G., and Wang, H. (2023). Research on path planning and control method for secondary autonomous cutting of cantilever roadheader in a large-section coal roadway. Sustainability, 15.10.3390/su15010560 ↗
7. Xu, Z., Liang, M., Fang, X., Wu, G., Chen, N., and Song, Y. (2022). Research on autonomous cutting method of cantilever roadheader. Energies, 15.10.3390/en15176190 ↗
8. Research on intelligent cutting control technology of transverse moving machine for large cross-section roadheader
9. Research on spiral angle optimization for longitudinal road header’s cutterhead10.1177/0954406220915491 ↗
10. Wang, S., and Wu, M. (2017, January 15–17). Study on influencing factors and autonomous correction method of roadheader cutting trajectory. Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) 2017, Chengdu, China.10.1109/ITNEC.2017.8284812 ↗
11. Qu, Y., Yang, T., Li, T., Zhan, Y., and Fu, S. (2022). Path tracking of underground mining boom roadheader combining BP neural network and state estimation. Appl. Sci., 12.10.3390/app12105165 ↗
12. Wang, S., Li, X., and Wu, M. (2018, January 9–11). Research on planning method of tunneling cutting trajectory with uncertain constraints. Proceedings of the 2018 Chinese Control And Decision Conference (CCDC) 2018, Shenyang, China.10.1109/CCDC.2018.8407577 ↗
13. Study on cutting trace planning of longitudinal roadheader and boundary control method
14. Ant colony optimization-based method for energy-efficient cutting trajectory planning in axial robotic roadheader10.1016/j.asoc.2024.111965 ↗
15. Study on Trajectory Planning and Control Method in Profile Cutting of Roadheader10.4028/www.scientific.net/AMR.139-141.1723 ↗
16. Solving multi-objective structural optimization problems using GDE3 and NSGA-II with reference points10.1016/j.engstruct.2021.112187 ↗
17. Data-driven RLV multi-objective reentry trajectory optimization based on new QABC algorithm10.1007/s00170-015-8124-9 ↗
18. Trajectory planning in joint space for a pointing mechanism based on a novel hybrid interpolation algorithm and NSGA-II algorithm10.1109/ACCESS.2020.3042890 ↗
19. Gao, Y., Cui, J., and Wang, N. (2024, January 6–8). Multi-Objective Drilling Trajectory Optimization Under Parameter Uncertainty. Proceedings of the 2024 4th International Conference on Computer Science and Blockchain (CCSB) 2024, Shenzhen, China.10.1109/CCSB63463.2024.10735605 ↗
20. Solving multiobjective constrained trajectory optimization problem by an extended evolutionary algorithm10.1109/TCYB.2018.2881190 ↗
21. Zhang, D., Zhang, Z., Li, Y., Wang, Y., Zhang, W., and Zhu, Y. (2024, January 8–10). An NSGA-II-based multi-objective trajectory planning method for autonomous driving. Proceedings of the 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) 2024, Tianjin, China.10.1109/CSCWD61410.2024.10580383 ↗
22. Machmudah, A., Shanmugavel, M., Parman, S., Manan TS, A., Dutykh, D., Beddu, S., and Rajabi, A. (2022). Flight Trajectories Optimization of Fixed-Wing UAV by Bank-Turn Mechanism. Drones, 6.10.3390/drones6030069 ↗
23. Comparative analysis of evolutionary algorithms for multi-objective travelling salesman problem
24. Laser beams-based localization methods for boom-type roadheader using underground camera non-uniform blur model10.1109/ACCESS.2020.3032368 ↗