ROV dynamic modeling and grasping algorithm for underwater control system of marine oil and gas
发布时间：2026-03-21点击次数：
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DOI码：10.1038/s41598-025-22640-9
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发表刊物：Scientific Reports
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关键字：Petroleum；Underwater；Control system；Virtual reality；Underwater robots；Binocular vision；Reinforcement learning；Capture；Underwater production control system
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摘要：Deepwater oil exhibits great difficulty and risk in extraction under complex marine environments and strong ocean currents, and the operation and maintenance of its underwater control system rely heavily on remote operation. Traditional control methods make it hard to satisfy the demands of extraction. Therefore, the study first proposes simulating the marine working environment using virtual technology and model the Remote Operated Vehicle (ROV) to optimize power allocation. Secondly, the robot grasping task is achieved by designing binocular vision stereo image matching and improving the Proximal Policy Optimization grasping algorithm to enhance its stability and operational success rate under turbulent disturbances. Finally, an underwater production simulation system is built to provide a virtualization platform for oil and gas development operations. The results show that ROV can effectively achieve propeller power distribution, and the amplitude error under different operating conditions is reduced by an average of about 25% compared to the traditional Saab Seaeye model, with a maximum of no more than 5%. The simulation effect is significant. And the robot grasping system designed by the research institute can autonomously complete tasks. After training, the positioning error is reduced by 41.6% and 74.7% compared to the Mask Region based Convolutional Neural Network (Mask R-CNN) algorithm and You Only Look Once algorithm, respectively, reaching a final height of 0.11m. The grasping success rate is still better than the comparative algorithm by more than 10% and more than 90% in strong flow environments, and it takes less time to improve overall performance significantly. The research method can provide a guarantee for the safety of deepwater operations in oil and gas fields, and reduce operation and maintenance costs and mining difficulties.
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是否译文：否
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发表时间：2025-11-27
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收录刊物：SCI、EI
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李远哲
职务：Professor
主要任职：
个人信息
- 博士生导师
硕士生导师 - 教师英文名称：Yuanzhe
- 教师拼音名称：liyuanzhe
- 电子邮箱：
- 所在单位：碳中和研究院
- 职务：Professor
- 学历：博士研究生毕业
- 办公地点：中国矿业大学(文昌校区) 教三楼 碳中和研究院
- 性别：男
- 联系方式：yuanzhe.li@cumt.edu.cn
- 学位：哲学博士学位
- 毕业院校：Nanyang Technological University
学术荣誉：
- 2025当选：江苏特聘教授
曾获荣誉：
- 2023-12-27新加坡国家级范畴三（CSE3）半导体行业专家 & 碳税 主任审核员
- 2023-12-27新加坡经管局资源效率补助（REG(E)）减碳项目 主任验证审核员
- 2025-11-11净零路径 (NetZero Pathway) 主任验证审核员
- 2025-02-28Verra 碳排放信用 VCS 主任审核员
- 2024-12-02碳中和 ISO14068认证 主任审核员
- 2024-11-27可持续性保证（ACSAP）认证资格 (AA1000注册)
- 2025-09-01ISO14067 产品碳认证 外部主任审核员
- 2024-03-04ISO14064 温室气体排放与碳核查 外部主任审核员（ANAB注册验证）
- 2025-10-01ISO50001 能源管理体系外部主任审员
- 2024-05-13ISO45001 职业健康安全管理体系外部主任审员 (CQI & IRCA注册)
- 2024-04-01ISO14001 环境管理体系 外部主任审核员 (CQI & IRCA注册)
- 2017-09-18新加坡人力部注册安全官（WSHO）
- 2025-09-01江苏特聘教授
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