考虑关节误差的平面并联机器人机构全局校准方法研究

IF 1.9 4区 计算机科学 Q3 ROBOTICS
Robotica Pub Date : 2024-09-16 DOI:10.1017/s0263574724000973
Qinghua Zhang, Huaming Yu, Lingbo Xie, Qinghua Lu, Weilin Chen
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引用次数: 0

摘要

为了提高工业机器人的定位精度,本文提出了一种考虑关节误差的平面并联机器人全局标定方法,解决了现有标定方法只考虑部分误差源、标定精度差的问题,提高了标定效率和机器人定位精度。因此,它提高了校准效率和机器人定位的整体精度。首先,建立超定方程与结构参数相结合的误差模型,分析各误差源的全局敏感性。根据激光跟踪仪的测量数据,用最小二乘法确定了局部误差源,使局部误差精度提高了 88.6%。然后,提出了基于反距离加权法的全局误差空间插值方法,全局精度提高了 59.16%。最后,设计了具有强非线性逼近函数的径向基函数神经网络误差预测模型用于全局校准,精度提高了 63.05%。实验结果验证了所提方法的有效性。本研究不仅为该实验平台的工程应用提供了技术支持,也为相关机器人平台精度的提高提供了理论指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study of a global calibration method for a planar parallel robot mechanism considering joint error

In order to improve the positioning accuracy of industrial robots, this paper proposes a global calibration method for planar parallel robot considering joint errors, which solves the problem that the existing calibration methods only consider part of the error sources and the calibration accuracy is poor, and improves the calibration efficiency and robot positioning accuracy. Consequently, it improves calibration efficiency and the overall precision of robot positioning. Firstly, the error model of overdetermined equations combined with structural parameters is established, and the global sensitivity of each error source is analyzed. Based on the measurement data of laser tracker, the local error source is identified by the least square method, which improves the local error accuracy by 88.6%. Then, a global error spatial interpolation method based on inverse distance weighting method is proposed, and the global accuracy is improved by 59.16%. Finally, the radial basis function neural network error prediction model with strong nonlinear approximation function is designed for global calibration, and the accuracy is improved by 63.05%. Experimental results verify the effectiveness of the proposed method. This study not only provides technical support for the engineering application of this experimental platform but also provides theoretical guidance for the improvement of the accuracy of related robot platforms.

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来源期刊
Robotica
Robotica 工程技术-机器人学
CiteScore
4.50
自引率
22.20%
发文量
181
审稿时长
9.9 months
期刊介绍: Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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