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基于自适应迭代的机器人曲面恒力跟踪

李琳 肖佳栋 张铁 肖蒙

李琳, 肖佳栋, 张铁, 等 . 基于自适应迭代的机器人曲面恒力跟踪[J]. 北京航空航天大学学报, 2019, 45(4): 641-649. doi: 10.13700/j.bh.1001-5965.2018.0441
引用本文: 李琳, 肖佳栋, 张铁, 等 . 基于自适应迭代的机器人曲面恒力跟踪[J]. 北京航空航天大学学报, 2019, 45(4): 641-649. doi: 10.13700/j.bh.1001-5965.2018.0441
LI Lin, XIAO Jiadong, ZHANG Tie, et al. Constant-force curved-surface-tracking with robotic manipulator based on adaptive iterative algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(4): 641-649. doi: 10.13700/j.bh.1001-5965.2018.0441(in Chinese)
Citation: LI Lin, XIAO Jiadong, ZHANG Tie, et al. Constant-force curved-surface-tracking with robotic manipulator based on adaptive iterative algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(4): 641-649. doi: 10.13700/j.bh.1001-5965.2018.0441(in Chinese)

基于自适应迭代的机器人曲面恒力跟踪

doi: 10.13700/j.bh.1001-5965.2018.0441
基金项目: 

国家科技重大专项 2015ZX04005006

广东省重大科技专项 2014B090921004

广东省重大科技专项 2014B090920002

中山市重大科技专项 2016F2FC0006

详细信息
    作者简介:

    李琳 女, 博士, 教授。主要研究方向:机器人技术及应用

    肖佳栋 男, 硕士研究生。主要研究方向:机器人打磨过程智能力控制

    张铁 男, 博士, 教授, 博士生导师。主要研究方向:机器人及自动化装备设计

    通讯作者:

    张铁, E-mail: merobot@scut.edu.cn

  • 中图分类号: TP242.2

Constant-force curved-surface-tracking with robotic manipulator based on adaptive iterative algorithm

Funds: 

National Science and Technology Major Project of China 2015ZX04005006

Science and Technology Planning Project of Guangdong Province, China 2014B090921004

Science and Technology Planning Project of Guangdong Province, China 2014B090920002

Zhongshan Science and Technology Planning Project, China 2016F2FC0006

More Information
  • 摘要:

    针对利用机器人进行打磨、抛光、去毛刺等场合时末端执行器对曲面工件轮廓跟踪时难以得到恒定接触力的问题,对机器人末端执行器和工件轮廓接触时的接触力进行研究,建立了实际跟踪过程中机器人末端执行器的接触力和已知传感器坐标系的映射关系,提出了一种基于自适应迭代学习算法的机器人力/位混合曲面恒力跟踪控制方法。该方法由两部分组成:基于机器人和环境接触时的阻抗模型设计了迭代学习控制律,在PD反馈控制的基础上通过迭代项克服机器人的未知参数和不确定性,并构建Lyapunov能量函数证明所提控制律的收敛性;将迭代学习控制律和力/位混合曲面恒力跟踪控制方法结合起来设计了用于曲面工件轮廓跟踪的控制方法。实验结果显示,经过15次迭代,接触力的波动范围逐渐变小并稳定在±3 N之内,验证了所提方法的有效性。

     

  • 图 1  机器人曲面恒力跟踪实验平台模型

    Figure 1.  Experimental platform model of robot constant-force curved-surface-tracking

    图 2  机器人模型末端局部图

    Figure 2.  Partial view of end-effector of robot model

    图 3  机器人末端受力分析

    Figure 3.  Analysis of force on robot end-effector

    图 4  基于自适应迭代学习算法的力/位混合控制

    Figure 4.  Hybrid force/position control based on adaptive iterative learning algorithm

    图 5  机器人曲面恒力跟踪实验平台

    Figure 5.  Experimental platform of robot constant-force curved-surface-tracking

    图 6  探头尺寸

    Figure 6.  Size of probe detector

    图 7  曲面工件尺寸

    Figure 7.  Size of curved-surface workpiece

    图 8  没有迭代的跟踪过程

    Figure 8.  Tracking process before iteration

    图 9  迭代1次、7次和15次的跟踪过程

    Figure 9.  Tracking process after 1 iteration, 7 iterations and 15 iterations

    图 10  工件曲线与实际跟踪曲线轨迹对比

    Figure 10.  Comparison between curve of workpiece and curve of tracking trajectory

    图 11  没有迭代与迭代15次之后的跟踪曲线轨迹对比

    Figure 11.  Comparison between curve of tracking trajectory without iteration and curve of tracking trajectory after 15 iterations

    表  1  误差分析

    Table  1.   Error analysis

    迭代次数 接触力/N
    误差绝对值平均值 误差标准差 误差方差
    0 4.179 8 2.423 4 5.872 6
    1 3.609 1 1.983 2 3.932 9
    2 3.063 5 2.218 6 4.922 1
    3 2.860 2 2.440 7 5.957 0
    4 2.522 3 2.079 6 4.324 8
    5 2.260 9 1.661 3 2.759 8
    6 1.997 8 2.002 7 2.010 8
    7 1.700 3 1.368 5 1.872 7
    8 1.613 2 1.283 5 1.647 4
    9 1.686 4 1.344 6 1.808 0
    10 1.475 7 1.224 4 1.499 1
    11 1.352 7 1.147 7 1.317 1
    12 1.326 1 1.144 1 1.384 4
    13 1.260 4 0.996 0 1.006 3
    14 1.021 7 0.976 3 0.953 1
    15 0.886 1 0.870 5 0.757 7
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-07-23
  • 录用日期:  2018-09-19
  • 刊出日期:  2019-04-20

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