面向轨迹动态感知与自主决策的工业机器人数字孪生建模方法研究

doi:10.3901/JME.2025.07.269

摘要/Abstract

摘要： 工业机器人是智能制造的重要装备，提高机器人感知和决策能力是工业机器人发展的必然趋势。由于工业机器人关节刚度较低导致动态性能不佳，在工作过程中实际轨迹与期望轨迹存在偏差，通常需要操作人员使用示教器根据实际运行轨迹进行长时间的调试。为了提高工业机器人工作轨迹精度和智能决策能力，提出了一种面向轨迹动态感知与自主决策的工业机器人数字孪生模型构建方法，设计了具备轨迹虚实交互能力的工业机器人数字孪生框架，运用机器人运行过程中的多源异构数据保障了孪生模型对物理实体轨迹的动态感知和实时映射。提出了基于轨迹容错范围阈值评价工业机器人工作轨迹准确性的方法，结合机器人孪生模型和轨迹误差模型建立了基于多项式函数的末端轨迹短时演化预测策略，实现了在实体机器人轨迹即将偏离期望轨迹时，通过数字孪生模型超前判断机器人轨迹偏离情况并自主决策，根据决策结果智能规划新的轨迹和控制机器人实体执行。最后在UR5机器人上验证了该方法的有效性，实现了基于演化预测的末端轨迹自主决策控制，提高了工业机器人轨迹控制智能化水平和鲁棒性。

关键词: 数字孪生, 工业机器人, 动态感知, 虚实交互, 自主决策

Abstract: Industrial robots are significant equipment for intelligent manufacturing, it is an essential trend for industrial robots to improve their perception and decision-making capability. As the joint stiffness of industrial robots is weak which results in poor dynamic performance, there is deviation between the actual trajectory and the desired trajectory during the working process, and it is generally necessary for the operator to use a teach pendant to debug the robot for a long time according to the actual running trajectory. In order to improve the trajectory accuracy and intelligent decision-making ability of industrial robots, this paper proposes a digital twin model construction method for industrial robots oriented to trajectory dynamic perception and autonomous decision-making, designs a digital twin framework for industrial robots with the ability of trajectory interaction between the real and the virtual, which ensures the dynamic perception and real-time mapping of the twin model on the trajectory of the physical entity by fusing the multi-origin heterogeneous in the process of the robot's operation. A method for evaluating the accuracy of industrial robot trajectory based on the trajectory error tolerance range threshold is proposed, and a polynomial function-based short-time evolution prediction strategy for the end trajectory is established by combining the robot twin model and trajectory error model, which implements an autonomous decision-making process to judge the deviation of the robot trajectory by the digital twin model when the trajectory of the physical robot is about to deviate from the desired trajectory. According to the decision result, a new trajectory is intelligently planned and the robot entity is controlled to execute. Finally, the effectiveness of the method is verified on the UR5 robot, which implements the evolutionary prediction-based autonomous decision-making control of the end trajectory, and improves the level of intelligence and robustness of the trajectory control of industrial robots.

Key words: digital twin, industrial robot, dynamic perception, virtual-reality interaction, autonomous decision-making

中图分类号:

TP391

李睿智, 陈悦敏, 闫纪红. 面向轨迹动态感知与自主决策的工业机器人数字孪生建模方法研究[J]. 机械工程学报, 2025, 61(7): 269-283.

LI Ruizhi, CHEN Yuemin, YAN Jihong. Digital Twin Modeling Method for Industrial Robots with Dynamic Trajectory Sensing and Autonomous Decision-making[J]. Journal of Mechanical Engineering, 2025, 61(7): 269-283.

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