Abstract
Compliance is essential for precision assembly, which provides motion guidance and damage avoidance. Force control can offer flexible implementation of active compliance for manipulators. In this paper, an active radial compliance method is developed for the insertion task of thin walled millimeter-sized cylinders. A radial force controller is designed to satisfy the contact force constraint in the component’s radial directions, which integrates the explicit force control with the high precision attitude measurement based on microscopic vision. An anisotropic stiffness learning method is proposed based on clustering and support vector machines. It can obtain the hidden anisotropic stiffness characteristics of the mechanical system from experience data. Experimental results verify the effectiveness of the proposed methods.
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Abbreviations
- v a :
-
attitude of component’s axis
- J :
-
image Jacobian matrix
- l :
-
vector in the image
- f r :
-
contact force in component’s radial direction
- f d :
-
desired contact force in component’s radial direction
- e f :
-
contact force error in component’s radial direction
- λ :
-
controller gain
- τ :
-
dead zone threshold of controller
- h :
-
insertion depth
- \({\tilde k_i}\) :
-
estimated stiffness of a sample
- k +, k - :
-
high and low stiffness in different directions
- C +, C - :
-
classes with high and low stiffness
- H, H A , H I+, H I- :
-
insertion depth region and its subregions
- w, b :
-
normal vector and offset of separating plane in SVM
- \(\tilde r\) :
-
geometric margin in SVM
- c :
-
penalty parameter in SVM
- d +, d − :
-
parameters determining boundary of fuzzy region
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Qin, FB., Xu, D., Xing, DP. et al. An active radial compliance method with anisotropic stiffness learning for precision assembly. Int. J. Precis. Eng. Manuf. 18, 471–478 (2017). https://doi.org/10.1007/s12541-017-0057-9
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DOI: https://doi.org/10.1007/s12541-017-0057-9