自主钻井和下一代深度矿产勘探的想法
George Nikolakopoulos1, Anton Koval1, Matteo Fumagalli1,2
1Department of Computer Science, Electrical and Space Engineering, Signals and Systems, Luleå University of Technology, 971 87 Luleå, Sweden.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
自主钻探提高了采矿安全和效率. 先进的AI和同时定位和绘制 (SLAM) 使机器人能够在复杂的地下矿山中进行深度矿物勘探.
科学领域:
- 机器人和自动化机器人与自动化
- 地质工程是地质工程.
- 人工智能的人工智能
背景情况:
- 远程钻井技术对于自动化硬岩采矿,提高效率和安全至关重要.
- 传统的导航系统在地下矿山中扎,需要先进的解决方案.
- 采矿行业正在转向人工智能驱动的系统,以实时决策.
研究的目的:
- 探索采矿中的自动化,重点是自动钻井设备和人工智能集成.
- 研究先进的数据收集和3D岩石硬度建模.
- 为在危险的采矿环境中提供地下导航和机器人勘探的解决方案.
主要方法:
- 集成先进的数据收集,用于监测钻探参数.
- 3D岩石硬度建模技术的开发.
- 同时定位和绘图 (SLAM) 的应用,用于地下导航.
- 设计用于危险地区的自主机器人勘探装置.
主要成果:
- 演示自主钻井装置的导航和有效钻探.
- 成功实施人工智能,用于钻井操作中的实时决策.
- 验证SLAM技术,以在具有挑战性的地下环境中提供可靠的导航.
- 机器人系统有可能彻底改变矿产勘探.
结论:
- 自主钻井系统显著提高了采矿的安全性和效率.
- 先进的AI和SLAM是使复杂的地下环境中的自主操作成为可能的关键.
- PERSEPHONE项目旨在提供用于深度矿产勘探的完全自主机器人系统.
关键词:
在LIBS分析中,LIBS分析在LoRaWAN网络中,在SLAM导航中使用SLAM导航.自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主钻探自主勘探钻探 钻探钻探模块化机器人系统 模块化机器人系统实时岩石传感感测试 实时岩石传感机器人协作 机器人协作地下采矿自动化 - - 地下采矿自动化相关概念视频
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