Kinematic sensitivity analysis of manipulators using a novel dimensionless index

被引:29
作者
Brahmia, Allaoua [1 ]
Kelaiaia, Ridha [1 ]
Company, Olivier [2 ]
Chemori, Ahmed [2 ]
机构
[1] Univ 20 aout 1955, LGMM Lab, PB N 26 Route Elhadaik, Skikda 21000, Skikda, Algeria
[2] Univ Montpellier, LIRMM, CNRS, Montpellier, France
关键词
Sensitivity analysis; New sensitivity index; PAR2; PKM; Position error modeling; Precision design; GEOMETRIC ERRORS; PARALLEL MANIPULATORS; MACHINE-TOOLS; IDENTIFICATION; COMPENSATION; CALIBRATION; ACCURACY; ROBOT;
D O I
10.1016/j.robot.2022.104021
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Geometric errors directly affect the position of the end-effector of a Parallel Kinematic Manipulator (PKM), thus reducing its positioning accuracy. However, the tasks that are performed by PKMs, such as high-precision machining using a kinematic model with nominal values, are affected by machine errors that are not taken into account. Therefore, it is important to make an accurate determination of a machine's error factors to obtain an accurate error model. Identifying the most crucial geometric errors and determining a method to control them is key in improving the accuracy of PKMs. To achieve this objective, a new method of sensitivity analysis, allowing the crucial geometric errors for parallel and serial manipulators to be identified, is proposed. A new dimensionless sensitivity index, based on the definition of a Local Sensitivity Index (LSI), is used to perform this analysis. The geometric error modeling is performed by deriving the position vector of the end-effector of the PKM. To test the efficiency of the proposed method, the main sources of PAR2 PKM errors are identified. The results show that 33.3% of the error components (main errors) from all error sources can be improved, to achieve a 51.8% improvement in the accuracy of the position error. These results indicate that the error sensitivity analysis method is quite effective, and can significantly contribute to improving the accuracy of a PKM. (c) 2022 Elsevier B.V. All rights reserved.
引用
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页数:10
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