Home Journals Articles Updates About
CN
image
收藏切换
A Path Planning Method Integrating Multi-Cost Constraints and Adaptive Smoothing for Deep-Sea Polymetallic Nodule Mining Vehicle
收藏切换
Weijie PENG1, Chen WANG2, Longde SU1, Xinshu LU1
Mining and Metallurgical Engineering | 2026, 46(3) : 40 - 45
Less
收藏切换
Mining and Metallurgical Engineering | 2026, 46(3): 40-45
• SPECIAL TOPIC ON BREAKTHROUGHS IN KEY TECHNOLOGIES AND COORDINATED DEVELOPMENT OF INDUSTRIAL CHAINS FOR DEEP-SEA MINERAL RESOURCE EXPLOITATION •
A Path Planning Method Integrating Multi-Cost Constraints and Adaptive Smoothing for Deep-Sea Polymetallic Nodule Mining Vehicle
Full
Weijie PENG1, Chen WANG2, Longde SU1, Xinshu LU1
Affiliations
  • 1.School of Mechanical Engineering, Guangxi University, Nanning 530004, Guangxi, China
  • 2.State Key Laboratory of Deepsea Manned Vehicle, China Ship Scientific Research Center, Wuxi 214082, Jiangsu, China
doi: 10.3969/j.issn.0253-6099.2026.03.004
Outline
收藏切换

Based on the slope-climbing dynamic analysis of mining vehicles, models for traction, total resistance and sinkage were established with the characteristics of soft deep-sea sediment taken into consideration, and a passable slope threshold was also determined. An improved A* path planning algorithm is proposed, which integrates multi-cost constraints to optimize the search efficiency and path quality, and employs a redundant node removal method and Bézier curve fitting for the post-processing smoothing of the path. Simulation results show that, compared with the traditional A* algorithm, the proposed improved algorithm makes the total length of the path planned shortened by about 3% on average, reduces the travel time and energy consumption costs by over 60% on average, and decreases the total steering angle of the path by over 70% on average. It generates a global path with a lower comprehensive cost and smoother steering, effectively improving the safety and efficiency of deep-sea mining vehicle operations.

deep-sea mining vehicle  /  path planning  /  A* algorithm  /  dynamic analysis  /  path smoothing  /  polymetallic nodule
彭帷杰, 王臣, 苏泷德, 陆薪树. 融合多代价约束与自适应平滑的深海结核采矿车路径规划方法. 矿冶工程杂志, 2026 , 46 (3) : 40 -45 . DOI: 10.3969/j.issn.0253-6099.2026.03.004
Weijie PENG, Chen WANG, Longde SU, Xinshu LU. A Path Planning Method Integrating Multi-Cost Constraints and Adaptive Smoothing for Deep-Sea Polymetallic Nodule Mining Vehicle[J]. Mining and Metallurgical Engineering, 2026 , 46 (3) : 40 -45 . DOI: 10.3969/j.issn.0253-6099.2026.03.004
Appendix
Less
Year 2026 volume 46 Issue 3
100
21
Cite this Article
BibTeX
Article Info
doi: 10.3969/j.issn.0253-6099.2026.03.004
  • Receive Date：2026-04-02
  • Online Date：2026-10-08
Article Data
Affiliations
History
  • Received：2026-04-02
Funding
Affiliations
    1.School of Mechanical Engineering, Guangxi University, Nanning 530004, Guangxi, China
    2.State Key Laboratory of Deepsea Manned Vehicle, China Ship Scientific Research Center, Wuxi 214082, Jiangsu, China
References
Share
https://castjournals.cast.org.cn/joweb/kygczz/EN/10.3969/j.issn.0253-6099.2026.03.004
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House