中国机械工程 ›› 2025, Vol. 36 ›› Issue (06): 1188-1197.DOI: 10.3969/j.issn.1004-132X.2025.06.006

• 机械基础工程 • 上一篇    下一篇

基于关节扭矩平衡的机器人末端负载建模及辨识

高贯斌1,2;赵思郭1,2;李映杰1,2*   

  1. 1.昆明理工大学机电工程学院,昆明,650500
    2.云南省智能控制与应用重点实验室,昆明,650500
  • 出版日期:2025-06-25 发布日期:2025-08-01
  • 作者简介:高贯斌,男,1979年生,教授、博士研究生导师。研究方向为机器人学、精密测量与控制、智能康复外骨骼。E-mail:gbgao@kust.edu.cn。
  • 基金资助:
    国家自然科学基金(52265001);云南省科技厅基础研究重点项目(202201AS070033)

Modeling and Identification of Robot End-payloads Based on Joint Torque Balance

GAO Guanbin1,2;ZHAO Siguo1,2;LI Yingjie1,2*   

  1. 1.Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,
    Kunming,650500
    2.Yunnan Key Laboratory of Intelligent Control and Application,Kunming,650500

  • Online:2025-06-25 Published:2025-08-01

摘要: 针对现有末端负载辨识方法质心参数解耦困难且难以在控制器不开放的机器人上实施的问题,提出了一种基于扭矩平衡的机器人末端负载建模及辨识方法。通过对关节扭矩平衡下的末端负载可辨识条件进行分析,构建了末端负载质量和质心位置的辨识模型。为解耦质量和质心参数,设计了一种依次辨识负载质量,质心位置x、y坐标,质心z坐标的三步辨识策略,并消除了辨识模型中扭矩投影带来的误差项。通过负载辨识的仿真和实验验证了所提方法的有效性,与不开源6自由度机器人自带辨识方法相比,质量辨识平均误差从0.103 kg减小至0.032 kg,质心位置辨识平均误差从50.25 mm减小至4.14 mm;与动力学参数辨识相比,质量辨识的平均误差从0.179 kg减小至0.083 kg,质心位置辨识平均误差从10.13 mm减小至4.33 mm。

关键词: 工业机器人, 末端负载, 扭矩平衡, 参数辨识, 力矩投影

Abstract:  To address the challenges of decoupling center of mass parameters in existing end-payload identification methods and the difficulty of implementation on robots with non-open controllers, a torque-balance-based modeling and identification method was proposed for robot end-payloads. The identifiability conditions of the end-payloads were analyzed under joint torque balance, and identification models for the end-payload mass and center of mass position were established. To further decouple the mass and center of mass parameters, a three-step identification strategy was designed, where the load mass was identified first, followed by the center of mass position in x and y, and finally in z. This strategy effectively eliminated the error terms introduced by the projection of joint torques in the identification models. The efficiency of the proposed method was validated through simulation and experiments. Compared with the built-in identification method of a non-open-source six-degree-of-freedom robot, the average error in mass identification is reduced from 0.103 kg to 0.032 kg, while the average error in center of mass position identification is decreased from 50.25 mm to 4.14 mm. Furthermore, compared with dynamics parameter identification, the mass identification error is reduced from 0.179 kg to 0.083 kg, and the center of mass position error is reduced from 10.13 mm to 4.33 mm.

Key words:  , industrial robot, end-payload, torque balance, parameter identification, torque projection

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