国内外巡检机器人研究进展与未来综述
Review on Research Progress and Future of Inspection Robot at Home and Abroad
DOI: 10.12677/airr.2026.151015, PDF,    科研立项经费支持
作者: 林祥文, 朱广蕊, 孙 景, 张春锋, 苏 杰:上海市动物无害化处理中心,上海
关键词: 巡检机器人技术演进理论分析发展趋势Inspection Robots Technological Evolution Theoretical Analysis Development Trends
摘要: 巡检机器人作为工业4.0时代的重要技术载体,在智能制造转型中发挥着关键作用。本文通过系统梳理国内外巡检机器人的理论发展脉络,深入分析其技术演进规律与应用特征。研究表明,巡检机器人技术正从单一功能向多元智能系统演进,从独立作业向人机协作转变。文章基于传感器技术、自主导航、数据处理、系统集成等核心技术理论,对比分析国内外发展差异,识别技术挑战与发展瓶颈,预判未来发展趋势。当前巡检机器人在温室农业、电力设备、畜禽养殖、基础设施等领域展现出广阔应用前景,但在复杂环境适应性、长期自主运行、多技术系统集成等方面仍面临挑战。未来发展将围绕人工智能深度融合、新材料技术应用、跨领域协同创新等方向展开,为智能制造和智慧城市建设提供重要技术支撑。
Abstract: Inspection robots have emerged as pivotal technological platforms in the Industry 4.0 era, playing a crucial role in the transformation toward intelligent manufacturing. This study systematically examines the theoretical development trajectory of inspection robots both domestically and internationally, conducting an in-depth analysis of their technological evolution patterns and application characteristics. Research findings reveal that inspection robot technology is transitioning from single-function systems toward multi-dimensional intelligent platforms, while simultaneously shifting from independent operations to human-robot collaborative frameworks. Drawing upon core technological theories encompassing sensor technology, autonomous navigation, data processing, and system integration, this research conducts a comparative analysis of developmental disparities between domestic and international approaches. The study identifies prevailing technical challenges and developmental bottlenecks while forecasting future evolutionary trends. Contemporary inspection robots demonstrate substantial application potential across diverse sectors including greenhouse agriculture, electrical equipment maintenance, livestock farming, and infrastructure monitoring. However, significant challenges persist in areas such as complex environment adaptability, long-term autonomous operation capabilities, and multi-technology system integration. Future developments are anticipated to center around the deep integration of artificial intelligence technologies, advanced material applications, and cross-disciplinary collaborative innovation. These advancements position inspection robots as essential technological foundations for both intelligent manufacturing initiatives and smart city construction endeavors.
文章引用:林祥文, 朱广蕊, 孙景, 张春锋, 苏杰. 国内外巡检机器人研究进展与未来综述[J]. 人工智能与机器人研究, 2026, 15(1): 146-155. https://doi.org/10.12677/airr.2026.151015

参考文献

[1] 王少聪, 杜肖鹏, 丁小明, 等. 温室巡检机器人关键技术研究进展与展望[J]. 江苏农业科学, 2024, 52(16): 1-10.
[2] 侯志华. 电气巡检机器人轨迹规划控制系统设计研究[J]. 机器人产业, 2024(4): 90-95.
[3] 肖德琴, 黄一桂, 熊悦淞, 等. 畜禽机器人技术研究进展与未来展望[J]. 华南农业大学学报, 2024, 45(5): 624-634+620.
[4] 高莉莉. 智能巡检机器人现状及发展趋势分析[J]. 农机使用与维修, 2023(10): 63-66.
[5] 高春艳, 陶渊, 吕晓玲, 张明路. 非结构化环境下巡检机器人环境感知技术研究综述[J]. 传感器与微系统, 2023, 42(4): 10-13+18.
[6] 李永立, 王燕飞. 国内外巡检机器人研究现状[J]. 科技创新与应用, 2022, 12(30): 66-68+72.
[7] 尹项迎, 蔺飞飞. 智能巡检机器人的现状与发展趋势[J]. 科技视界, 2020(24): 160-162.
[8] 彭道刚, 赵晨洋, 戚尔江. 基于准模型校准卡尔曼滤波的巡检机器人运动系统辨识研究[J]. 电气传动, 2020, 50(4): 74-80.
[9] 张成巍, 岳湘. 智能巡检机器人研究现状与发展趋势[J]. 电工文摘, 2015(1): 9-12.
[10] Choi, S., Al-Sabbag, Z.A., Narasimhan, S. and Yeum, C.M. (2024) Gaze-Based Human-Robot Interaction System for Infrastructure Inspections. 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, 13-17 May 2024, 9571-9577. [Google Scholar] [CrossRef
[11] Zhang, Y., Yang, Y., Lu, S. and Zhou, E. (2024) Development and Outlook for Pipeline Inspection Robots. Recent Patents on Engineering, 18, 16. [Google Scholar] [CrossRef
[12] 李铭浩, 于音, 李响, 等. 多模态全光智能机器人巡检系统设计[J]. 光学与光电技术, 2024, 22(3): 109-119.
[13] 金大刚, 毛青海, 陈自强, 等. 基于多能物联的水电站智能巡检机器人研究[J]. 电器工业, 2023(1): 62-65.
[14] 余浩扬, 李艳生, 肖凌励, 等. 面向动态环境的巡检机器人轻量级语义视觉SLAM框架[J]. 电子与信息学报, 2025, 47(10): 3979-3992.
[15] 吴张勇, 纪书保. 基于挂轨机器人的智能巡检系统研究[J]. 现代信息科技, 2024, 8(8): 60-63.
[16] 许钟奇. 铁矿井下钢丝绳巡检机器人设计与研究[D]: [硕士学位论文]. 北京: 中国矿业大学, 2023.
[17] 曹云虎. 智能机器人在变电站自动巡检系统中的应用探究[J]. 电脑爱好者(电子刊), 2023(6): 2808-2809.
[18] 柳翔, 刘雨佳, 李倩. 巡检轨道机器人管理系统关键技术研究[J]. 通讯世界, 2023, 30(4): 160-162.
[19] 张宝. 化工环境下巡检机器人关键控制技术研究进展[J]. 当代化工研究, 2023(22): 9-11.