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智能机器人在复杂隧道施工环境中的应用现状及适应性研究

刘志锋,  何红曈,  陈臣,  王旌,  张吉哲

刘志锋, 何红曈, 陈臣, 王旌, 张吉哲. 智能机器人在复杂隧道施工环境中的应用现状及适应性研究[J]. 岩土工程技术, 2026, 40(5): 657-663. doi: 10.20265/j.cnki.issn.1007-2993.2025-0275
引用本文: 刘志锋, 何红曈, 陈臣, 王旌, 张吉哲. 智能机器人在复杂隧道施工环境中的应用现状及适应性研究[J]. 岩土工程技术, 2026, 40(5): 657-663. doi: 10.20265/j.cnki.issn.1007-2993.2025-0275
LIU Zhifeng, HE Hongtong, CHEN Chen, WANG Jing, ZHANG Jizhe. Current status and adaptability research of intelligent robots in complex tunnel construction environments[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2026, 40(5): 657-663. doi: 10.20265/j.cnki.issn.1007-2993.2025-0275
Citation: LIU Zhifeng, HE Hongtong, CHEN Chen, WANG Jing, ZHANG Jizhe. Current status and adaptability research of intelligent robots in complex tunnel construction environments[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2026, 40(5): 657-663. doi: 10.20265/j.cnki.issn.1007-2993.2025-0275

智能机器人在复杂隧道施工环境中的应用现状及适应性研究

doi: 10.20265/j.cnki.issn.1007-2993.2025-0275
基金项目: 国家重点研发计划(2022YFB2603303);山东省交通运输厅科技计划项目(2021B101);济南市“新高校20条”资助项目(20228054)
详细信息
    作者简介:

    刘志锋,男,1991年生,硕士,高级工程师,主要从事城市轨道交通勘测方面的研究。E-mail:690851999@qq.com

    通讯作者:

    王 旌,男,1990年生,博士,教授,主要从事盾构隧道智能建造与灾害防控的研究。E-mail:wjingsdu@163.com

  • 中图分类号: TU455.4;TU69

Current status and adaptability research of intelligent robots in complex tunnel construction environments

  • 摘要: 隧道施工环境极为复杂,传统的人工及机械施工方式效率低、主观性强,智能机器人凭借其先进的感知、决策和执行能力,极大提高了复杂环境下隧道工程的施工精度和可靠性。为了研究智能机器人对复杂隧道施工环境的适应性,在总结国内外应用现状的基础上,对复杂隧道施工环境特点进行了详细分析,明确了地质条件复杂、空间受限以及环境恶劣等因素对智能机器人作业的影响。从工程案例出发,展示了智能机器人在提高隧道施工效率、提升质量和保障安全等方面的优势,探究了导航与定位精度、通信稳定性、能源供应与续航能力等影响智能机器人适应性的技术影响因素,以及施工工艺匹配度和与其他设备协同作业能力等工程影响因素,提出包括定制化设计和加强设备间协同作业标准化等策略,确保智能机器人能够更好地适应复杂隧道施工环境和工艺要求,提高隧道施工效率和安全性。

     

  • 图  1  AI智能安全巡查机器人

    Figure  1.  AI-powered intelligent security inspection robot

    图  2  凿岩机器人

    Figure  2.  Rock drilling robot

    图  3  喷浆机器人

    Figure  3.  Shotcrete robot

    图  4  监控量测机器人

    Figure  4.  Monitoring and measuring robot

    图  5  巡检机器人

    Figure  5.  Inspection robot

    图  6  钻爆法施工与智能机器人配合流程图

    Figure  6.  Flowchart of drilling and blasting construction coordinated with intelligent robots

    表  1  凿岩机器人前后施工效率

    Table  1.   Construction efficiency before and after using rock-drilling robots

    对比项目 每个循环进尺/m
    钻孔精度/mm 施工人员数量/人
    人工凿岩 1.6 ±50 8
    凿岩机器人 4 ±15 2
    变化情况 提高150% 精度提高 700% 减少75%
    下载: 导出CSV

    表  2  湿喷机和拱架机器人前后施工质量对比

    Table  2.   Comparison of construction quality before and after using the wet shotcreting machine and the arch robot

    对比项目湿喷每小时
    喷射量/m3
    湿喷回
    弹率/%
    每榀拱架安装
    时间/min
    每榀拱架安装
    施工人员数量
    人工作业1025609
    机器人作业3010203
    变化情况提高200%降低60%缩短66%减少66%
    下载: 导出CSV

    表  3  智能机器人与其他设备协同作业标准和规范

    Table  3.   Standards and specifications for collaborative operation between intelligent robots and other equipment

    协同作业环节通信要求作业顺序安全注意事项
    隧道开挖采用工业以太网通信,挖掘机器人实时向装载机和运输车辆发送挖掘进度和位置信息,装载机和运输车辆及时反馈自身状态信息挖掘机器人先进行挖掘,达到一定量后,装载机进行装载,运输车辆等待装载,装载完成后运输车辆运出岩石挖掘机器人作业时,周围严禁其他人员和设备靠近;装载机和运输车辆行驶过程中,保持安全距离,遵守交通规则
    初期支护通过 OPC UA 协议实现湿喷机器人、拱架机器人与其他支护设备的数据交互,实时调整作业参数先进行拱架安装,拱架安装完成后,湿喷机器人进行喷射混凝土作业湿喷机器人喷射作业时,确保喷头方向正确,避免混凝土飞溅伤人;拱架机器人作业时,注意防止拱架掉落
    隧道检测建立专用的无线通信网络,检测机器人与控制中心实时通信,上传检测数据检测机器人按照预定路线进行检测,检测完成后将数据传输给控制中心进行分析处理检测机器人在隧道内行驶时,设置警示标志,防止其他设备碰撞;控制中心及时对检测数据进行分析,发现问题及时通知相关人员处理
    下载: 导出CSV
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出版历程
  • 收稿日期:  2025-06-20
  • 修回日期:  2025-10-29
  • 录用日期:  2025-11-11
  • 网络出版日期:  2026-10-08
  • 刊出日期:  2026-10-08

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