数字孪生工业机器人：概念框架、关键技术与案例研究

doi:10.16182/j.issn1004731x.joss.25-0230

系统仿真学报 ›› 2025, Vol. 37 ›› Issue (7): 1723-1752.doi: 10.16182/j.issn1004731x.joss.25-0230

• 特约综述 • 上一篇

数字孪生工业机器人：概念框架、关键技术与案例研究

刘永奎¹, 杨康¹, 脱奔奔¹, 潘亚铎¹, 王欣宇¹, 王一涵¹, 龚永乾¹, 张霖², 王力翚³, 林廷宇⁴, 訾斌¹, 李元⁵, 游玮⁶, 徐旬⁷

^1.西安电子科技大学机电工程学院，陕西西安 710071
^2.北京航空航天大学自动化科学与电气工程学院，北京 100191
^3.瑞典皇家理工学院生产工程系，斯德哥尔摩 10044
^4.北京市复杂产品先进制造系统工程技术研究中心北京仿真中心，北京 100854
^5.合肥工业大学机械工程学院，安徽合肥 230009
^6.埃夫特智能装备股份有限公司，安徽芜湖 241007
^7.奥克兰大学机械工程系，奥克兰 1142

收稿日期:2025-03-25 修回日期:2025-05-28 出版日期:2025-07-18 发布日期:2025-07-30
第一作者简介:刘永奎(1981-)，男，教授，博士，研究方向为具身智能机器人、数字孪生工业机器人、人形机器人、智能制造。
基金资助:
国家重点研发计划(2024YFB4709400);陕西省自然科学基础研究计划(2025JC-YBMS-669)

Digital Twinned Industrial Robot: Conceptual Framework, Key Technologies, and Case Study

Liu Yongkui¹, Yang Kang¹, Tuo Benben¹, Pan Yaduo¹, Wang Xinyu¹, Wang Yihan¹, Gong Yongqian¹, Zhang Lin², Wang Lihui³, Lin Tingyu⁴, Zi Bin¹, Li Yuan⁵, You Wei⁶, Xu Xun⁷

^1.School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China
^2.School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
^3.Department of Production Engineering, KTH Royal Institute of Technology, Stockholm 10044, Sweden
^4.Beijing Complex Product Advanced Manufacturing Engineering Research Center, Beijing Simulation Center, Beijing 100854, China
^5.School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China
^6.Efort Intelligent Equipment Co. , Ltd. , Wuhu 241007, China
^7.Department of Mechanical Engineering, The University of Auckland, Auckland 1142, New Zealand

Received:2025-03-25 Revised:2025-05-28 Online:2025-07-18 Published:2025-07-30

摘要/Abstract

摘要：

为有效提升工业机器人价值及其全生命周期管理水平，将数字孪生与工业机器人进行深度融合，探讨一种新的工业机器人概念——数字孪生工业机器人。阐述数字孪生工业机器人的概念、构成和典型特征，并提出数字孪生工业机器人的体系架构。从“设计-制造-运维-退役”全生命周期的角度，系统梳理数字孪生工业机器人的关键技术。通过案例研究验证所提概念框架的有效性。总结并探讨数字孪生工业机器人的未来发展趋势。

关键词: 数字孪生, 工业机器人, 数字孪生工业机器人, 全生命周期

Abstract:

To effectively enhance the value and full life cycle management level of industrial robots, this paper integrated deeply digital twin with industrial robots and discussed a new concept, namely digital twinned industrial robot (DTIR). It defined the concept, composition, and typical characteristics of DTIRs and proposed their system architecture. From the perspective of the full life cycle of "design, manufacturing, operation and maintenance, and decommissioning", the key technologies of DTIRs were systematically sorted out. Furthermore, the validity of the proposed conceptual framework was verified through a case study. Finally, the paper summarized the findings and discussed the future development trends of DTIRs.

Key words: digital twin, industrial robot, digital twinned industrial robot, full life cycle

中图分类号:

TP391

刘永奎,杨康,脱奔奔等 . 数字孪生工业机器人：概念框架、关键技术与案例研究[J]. 系统仿真学报, 2025, 37(7): 1723-1752.

Liu Yongkui,Yang Kang,Tuo Benben,et al . Digital Twinned Industrial Robot: Conceptual Framework, Key Technologies, and Case Study[J]. Journal of System Simulation, 2025, 37(7): 1723-1752.

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模型类型	功能	构建方法	具体应用
多层级装配模型	以机器人的本体构成分析为基础，用于指导其他模型(如三维几何模型、多领域耦合模型等)的装配	结构树、知识图谱等	装配方案生成、可视化展示、虚拟调试等
多领域耦合模型	能够实现工业机器人“机-电-控”多领域耦合的高保真仿真和分析，从而支撑DTIR相关服务功能的开发	多软件协同建模方法、基于高层体系结构的建模方法、基于统一建模语言的建模方法等	高保真仿真及分析、优化设计、预测性维护等
运动学模型	描述和分析工业机器人位置和运动的关系	D-H参数法、几何分析法、旋量方法等	位置控制、运动仿真、人机协作等
动力学模型	描述和分析工业机器人运动和力(力矩)的关系	牛顿-欧拉法、拉格朗日法等	前馈控制、碰撞检测、力控作业等
物理模型	基于物理建模的方法对工业机器人整机及核心零部件进行受力分析、疲劳分析、多物理场耦合分析等	解析建模方法、数值建模方法等	优化设计、预测性维护等
数据驱动模型	基于数据分析的方法对工业机器人采集的数据进行建模以反映其行为和性能等特性	统计模型、机器学习、深度学习等	优化设计、预测性维护等

关节	电机功率/W	伺服驱动器电流/A	最大速度/((˚)/s)	关节允许范围/(˚)	传动方式	减速器(减速比)	数据采集
J1	400	6	330	±170	减速器	谐波减速器(80)	振动、角度、速度、加速度、跟随误差、电机电流、母线电压、电机力矩、电机温度、编码器温度、整机系统电压、电流、能耗、环境温度等
J2	400	6	330	±110	减速器	谐波减速器(80)
J3	200	6	330	+30~-220	减速器+同步带	谐波减速器(80)
J4	400	3	260	±180	减速器+同步带	谐波减速器(50)
J5	400	3	420	±110	减速器+同步带	谐波减速器(100)
J6	400	3	500	±360	减速器	谐波减速器(100)

数字孪生工业机器人：概念框架、关键技术与案例研究

Digital Twinned Industrial Robot: Conceptual Framework, Key Technologies, and Case Study

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