• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2026, Vol. 62 ›› Issue (9): 42-51.doi: 10.3901/JME.260406

• 机器人及机构学 • 上一篇    

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五轴混联机器人的运动学标定方法

张海峰1, 韩广超2, 叶伟1, 李秦川1   

  1. 1. 浙江理工大学机械工程学院 杭州 310018;
    2. 烟台清科嘉机器人联合研究院有限公司 烟台 264000
  • 收稿日期:2025-09-19 修回日期:2025-12-25 发布日期:2026-07-08
  • 作者简介:张海峰,男,1996年出生,博士研究生。主要研究方向为混联机器人运动学标定、建模与控制。E-mail:zhanghf5688@163.com;韩广超,男,1989年出生,硕士,中级工程师。主要研究方向为结构设计、有限元分析。E-mail:854436978@qq.com;叶伟,男,1988年出生,博士,副教授。主要研究方向为并联机构学。E-mail:wye@zstu.edu.cn;李秦川(通信作者),男,1975年出生,博士,教授。主要研究方向为并联机器人机构学和应用技术。发表论文30余篇。E-mail:lqchuan@zstu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(51935010)。

Kinematic Calibration Method for a Five-axis Hybrid Robot

ZHANG Haifeng1, HAN Guangchao2, YE Wei1, LI Qinchuan1   

  1. 1. School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018;
    2. Tsingke+ Research Institute, Yantai 264000
  • Received:2025-09-19 Revised:2025-12-25 Published:2026-07-08

摘要: 在精密加工制造领域,精度问题一直是五轴混联机器人面临的主要挑战之一。鉴于其结构内误差传递途径的广泛性与多样性,构建精确的整体误差模型显得尤为艰巨。针对这一难题,提出了一种五轴混联机器人的运动学标定方法。首先,将五轴混联机器人分解为刀具运动链和工件运动链,以减少相互之间的干扰和误差传递。其次,对包含并联机器人的刀具运动链构建闭环矢量方程,并对其进行微分摄动获取误差模型。通过引入一个辅助测量装置对并联机器人末端进行全位姿测量,由于末端位置/姿态误差具有各向异性,导致辨识结果不准确。为解决该问题,引入加权矩阵建立具有各向同性残差的辨识方程,从而提高辨识精度。而后,对工件运动链进行误差分析和建模,并将误差源分解为运动误差和零位误差,分别通过标定和对刀流程进行补偿。最后,通过标定以及试件加工实验验证了所提标定算法的有效性。结果表明,通过上述方法对刀具运动链和工件运动链进行运动学标定,可以有效地提高机床的运动精度和稳定性,从而满足制造领域对高精度加工的需求。

关键词: 五轴混联机器人, 误差建模, 运动学标定, 误差辨识

Abstract: The accuracy of five-axis hybrid robots is one of the primary challenges they face in the field of precision machining and manufacturing. Due to the complexity and diversity of error propagation paths within its structure, constructing an accurate overall error model is particularly challenging. To address this issue, this study proposes a kinematic calibration method for five-axis hybrid robots. First, decompose the five-axis hybrid robot into a tool motion chain and a workpiece motion chain to reduce interference and error propagation between them. Next, a closed-loop vector equation is constructed for the tool motion chain, which includes a parallel mechanism, and the error model is derived through differential perturbation. By introducing an auxiliary measurement device to perform full pose measurements on the end-effector of the parallel robot, it is noted that the anisotropy of the end-effector's position/orientation errors leads to inaccurate identification results. To resolve this issue, a weighted matrix is introduced to establish an identification equation with isotropic residuals, thereby improving identification accuracy. Subsequently, error analysis and modeling are performed for the workpiece motion chain, and the error sources are decomposed into motion errors and zero-point errors, which are compensated through the calibration and tool alignment processes, respectively. Finally, the effectiveness of the proposed calibration algorithm is validated through both calibration and test workpiece machining experiments. The results show that by calibrating the tool and workpiece motion chains, the proposed method can significantly improve the robot’s motion accuracy and stability, thus meeting the high-precision machining requirements in the manufacturing field.

Key words: five-axis hybrid robot, error modeling, kinematic calibration, error identification

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