【24h】

Identification of the manipulator stiffness model parameters in industrial environment

机译:工业环境中机械臂刚度模型参数的辨识

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

The paper addresses a problem of robotic manipulator calibration in real industrial environment. The main contributions are in the area of the elastostatic parameter identification. In contrast to other works the considered approach takes into account the elastic properties of both links and joints. Particular attention is paid to the practical identifiability of the model parameters, which completely differs from the theoretical one that relies on the rank of the observation matrix only, without taking into account essential differences in the model parameter magnitudes and the measurement noise impact. This problem is relatively new in robotics and essentially differs from that arising in geometrical calibration. To solve the problem, physical algebraic and statistical model reduction methods are proposed. They are based on the stiffness matrix sparseness taking into account the physical properties of the manipulator elements, structure of the observation matrix and also on the heuristic selection of the practically non-identifiable parameters that employ numerical analyses of the parameter estimates. The advantages of the developed approach are illustrated by an application example that deals with the elastostatic calibration of an industrial robot in a real industrial environment. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文解决了实际工业环境中机器人操纵器校准的问题。主要贡献在于弹性参数识别领域。与其他工作相比,考虑的方法考虑了链节和接头的弹性特性。特别要注意模型参数的实际可识别性,它与仅依赖观察矩阵等级的理论模型完全不同,而没有考虑模型参数幅度和测量噪声影响的本质差异。这个问题在机器人技术中相对较新,并且与几何校准中出现的问题本质上不同。为了解决这个问题,提出了物理代数和统计模型的简化方法。它们基于刚度矩阵稀疏性,其中考虑到操纵器元素的物理属性,观察矩阵的结构,还基于对采用参数估计值进行数值分析的几乎无法识别的参数的启发式选择。通过一个在实际工业环境中处理工业机器人的静电定标的应用示例,可​​以说明该开发方法的优势。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号