工业机器人位姿误差空间IDSW插值补偿方法研究

陈宵燕; 张秋菊; 孙沂琳; 陈海卫

doi:10.13433/j.cnki.1003-8728.2017.0309

工业机器人位姿误差空间IDSW插值补偿方法研究

doi: 10.13433/j.cnki.1003-8728.2017.0309

陈宵燕^1,2,
张秋菊^1,2, ,,
孙沂琳^1,2,
陈海卫^1,2

1.
江南大学机械工程学院, 江苏无锡 214122;
2.
江苏省食品先进制造装备与技术重点实验室, 江苏无锡 214122

基金项目:

国家自然科学基金项目（51575236）资助

详细信息

作者简介:
陈宵燕(1990-),博士研究生,研究方向为机器人基础与应用集成技术,15261596656@163.com

通讯作者:
张秋菊(联系人),教授,博士生导师,zhangqiuj@jiangnan.edu.cn

计量
- 文章访问数: 206
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- PDF下载量: 7
- 被引次数: 0
出版历程
- 收稿日期: 2015-07-16
- 刊出日期: 2017-03-05

Space IDSW Interpolation Compensation Method of Position and Orientation Error of Industrial Robot

Chen Xiaoyan^1,2,
Zhang Qiuju^{1,2
, ,},
Sun Yilin^1,2,
Chen Haiwei^1,2

1.
School of Mechanical Engineering, Jiangnan University, Jiangsu Wuxi 214122, China;
2.
Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Jiangsu Wuxi 214122, China

摘要

摘要: 探讨了工业机器人误差模型及位姿误差补偿的现有方法；对基于空间插值的补偿方法进行研究，提出机器人位置和机器人位姿误差两者之间的高度相关性是插值补偿法有效的先决条件；对利用微分法建立的机器人位姿误差模型进行研究，得到在机器人末端姿态不变时任意两点的位置误差的差值和姿态误差的差值分别与该两点位置差值呈高度线性关系；提出一种基于均匀数据场的空间IDSW（反距离平方加权）插值算法的机器人位姿误差补偿方法，并设计对比实验，仿真验证了本文所提出方法的有效性。
- 误差模型 /
- 位姿补偿 /
- 线性关系 /
- 均匀数据场 /
- 反距离平方加权
Abstract: The industrial robot error models and the existing methods of position and orientation compensation are investigated. The compensation method based on spatial interpolation is studied, and it is found that the high correlation between the robot end pose error and the robot end position is a necessary factor for this method. The geometric error model derived by differential method is obtained, and the high linear dependency between the pose error of two points and the correspondent distance is achieved when the orientation of robot is fixed; Finally, a position and orientation compensation method is proposed based on uniform grid and algorithm of space IDSW (Inverse distance squared weighting) interpolation, and comparative experiments are design and tested to verify the effectiveness of the proposed method.
- models /
- position and orientation compensation /
- linear dependency /
- uniform grid /
- inverse distance squared weighting

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