对于海洋石油和天然气的水下控制系统的ROV动态建模和掌握算法
Yuhang Li1, Sunwei Li2, Yuanzhe Li3
1Ocean Building, Tsinghua Shenzhen International Graduate School, Taoyuan Subdistrict, Nanshan District, Shenzhen, 518055, Guangdong, China. liyuhangkelite@163.com.
Scientific reports
|November 27, 2025
概括
这项研究提高了深水石油开采的安全性和效率. 它优化了远程操作车辆 (ROV) 的功率,并在具有挑战性的海洋条件下提高了机器人的抓捕稳定性.
科学领域:
- 海洋工程 海洋工程
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
背景情况:
- 由于恶劣的海洋环境和强烈的海流,深水石油开采面临重大风险.
- 水下控制系统在很大程度上依赖于远程操作,传统方法证明不足.
研究的目的:
- 在海洋环境中优化远程操作车辆 (ROV) 的功率分配.
- 提高机器人在动荡条件下掌握任务的稳定性和成功率.
- 为水下石油和天然气开发业务开发一个虚拟平台.
主要方法:
- 使用虚拟技术模拟海洋环境,并为功率优化而建模ROV.
- 实施双眼视觉立体图像匹配,并改进近距离政策优化以获取.
- 构建一个用于虚拟化的水下生产模拟系统.
主要成果:
- 优化了ROV螺旋功率分配,与传统模型相比,幅度误差平均减少了25%.
- 机器人抓取系统实现了较少的定位错误 (41.6%对比41.6%). 面具R-CNN,74.7%与YOLO相比). 这是一个很好的例子.
- 把握成功率超过了比较算法超过10%和90%在强流中,任务完成时间缩短.
结论:
- 开发的方法显著提高了ROV动力分配和机器人深水作业中的抓取能力.
- 虚拟模拟系统为增强石油和天然气开发提供了一个强大的平台.
- 这项研究为更安全,更具成本效益和更轻松的深水作业提供了途径.
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