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轮毂锻造机器人欠秩耦合端拾器结构设计及优化

袁明新 张全兵 申一虎 申燚

袁明新, 张全兵, 申一虎, 申燚. 轮毂锻造机器人欠秩耦合端拾器结构设计及优化[J]. 机械科学与技术, 2022, 41(8): 1197-1204. doi: 10.13433/j.cnki.1003-8728.20200438
引用本文: 袁明新, 张全兵, 申一虎, 申燚. 轮毂锻造机器人欠秩耦合端拾器结构设计及优化[J]. 机械科学与技术, 2022, 41(8): 1197-1204. doi: 10.13433/j.cnki.1003-8728.20200438
YUAN Mingxin, ZHANG Quanbing, SHEN Yihu, SHEN Yi. Structural Design and Optimization of Under-rank Coupling End Picker for Forging Robot[J]. Mechanical Science and Technology for Aerospace Engineering, 2022, 41(8): 1197-1204. doi: 10.13433/j.cnki.1003-8728.20200438
Citation: YUAN Mingxin, ZHANG Quanbing, SHEN Yihu, SHEN Yi. Structural Design and Optimization of Under-rank Coupling End Picker for Forging Robot[J]. Mechanical Science and Technology for Aerospace Engineering, 2022, 41(8): 1197-1204. doi: 10.13433/j.cnki.1003-8728.20200438

轮毂锻造机器人欠秩耦合端拾器结构设计及优化

doi: 10.13433/j.cnki.1003-8728.20200438
基金项目: 

2018年国家重点研发计划"智能机器人"重点专项 2018YFB1309100

2019年江苏省科技成果转化专项资金项目 BA2019092

详细信息
    作者简介:

    袁明新(1978-), 副教授, 博士, 研究方向为机器人技术、多机器人系统, mxyuan78@163.com

  • 中图分类号: TP241

Structural Design and Optimization of Under-rank Coupling End Picker for Forging Robot

  • 摘要: 为了提高高温和振动环境中轮毂锻造机器人的夹持稳定性和安全性, 设计了一种轮毂锻造机器人欠秩耦合端拾器, 并进行了结构优化。首先, 将欠秩端拾器与弹簧杆件耦合, 进行了欠秩耦合端拾器的设计及其自适应抓取过程分析; 然后基于虚功原理, 建立了端拾器执行机构在自适应夹持状态下的接触力模型; 随后以接触力大小均衡性为要求建立结构参数优化模型, 并提出新自适应小世界算法及其优化流程; 最后利用自适应小世界优化算法完成了端拾器优化, 并将优化结果与经验法、Fmincon优化函数、遗传算法和基本小世界算法进行了比较。数值测试表明, 与其他4种算法相比, 自适应小世界算法的优化目标值最小, 且分别减少了97.4%、62.9%、52.3%和42.2%, 显示出小世界算法在欠秩耦合端拾器优化中的可行性和优越性; 而将所优化结构参数分别代入端拾器的接触力模型比较, 文中所优化端拾器不同接触点处接触力偏差最大值也最小, 且最大偏差分别减少了87.2%、82.6%、69.5%和42.1%, 满足了锻造机器人端拾器夹持时的接触力均衡性要求。
  • 图  1  轮毂锻造机器人欠秩耦合端拾器

    图  2  欠秩耦合端拾器单手指自适应夹取过程

    图  3  欠秩耦合端拾器自适应夹取

    图  4  欠秩耦合端拾器几何模型和静力学模型

    图  5  PL随迭代进程变化曲线

    图  6  4种智能优化方法进化曲线

    表  1  5种算法的端拾器优化对比

    算法 minf(X) σmax/ % h1/ mm h2/ mm h3/ mm a2/ mm a3/ mm a4/ mm a5/ mm β1/ rad β2/ rad β3/ rad γ1/ rad γ2/ rad α1/ rad φ2/ rad
    经验法 5.453 6× 10-2 48.4 55 35 25 70 60 50 40 1.5 1.5 0.6 0.6 1.5 0.8 1.2
    FOF 平均 4.313 3× 10-3 - - - - - - - - - - - - - - -
    最优 3.7847× 10-3 35.6 68.824 51.833 65.970 37.141 11.178 59.341 1.388 39.742 0.876 0.981 0.764 0.827 0.683 1.279
    GA 平均 3.3153× 10-3 - - - - - - - - - - - - - - -
    最优 2.946 7× 10-3 20.3 70.322 53.655 76.571 57.067 14.792 60.960 1.048 59.651 0.731 1.239 0.768 0.866 0.778 1.531
    SWA 平均 2.7324× 10-3 - - - - - - - - - - - - - - -
    最优 2.429 4× 10-3 10.7 65.266 48.471 57.502 37.975 10.812 60.944 1.291 56.515 0.418 1.098 0.727 0.996 0.554 1.387
    ASWA 平均 1.620 4× 10-3 - - - - - - - - - - - - - - -
    最优 1.4042× 10-3 6.2 54.991 53.957 78.054 45.861 9.959 78.592 1.242 54.601 0.776 1.079 0.885 1.249 0.3678 1.211
    下载: 导出CSV
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  • 收稿日期:  2020-09-15
  • 刊出日期:  2022-08-25

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