Abstract
This paper proposes a partition of unity method (PUM) based on KDFCM (KDFcmPUM) that can be implemented to solve the dense matrix problem that occurs when the radial basis function (RBF) interpolation method deals with a large amount of scattered data. This method introduces a kernel fuzzy clustering algorithm to improve clustering accuracy and achieve the partition of unity. The local compact support RBF is used to construct the weight function, and local expression is obtained from the interpolation of the global RBF. Finally, the global expression is constructed by the weight function and local expression. In this paper, the method is applied to the orthogonally splitting imaging pose sensor to establish the mathematical model and the calibration and test experiments are carried out. The calibration and test accuracy both reached ±0.1 mm, and the number of operations was reduced by 4% at least. The experimental results show that KDFcmPUM is effective.
Highlights
In order to achieve pose measurement with a wide range and high precision, the orthogonally splitting imaging pose sensor uses dual linear CCDs to simulate a single array CCD
This paper proposes a partition of unity method based on KDFcm that can reflect the distribution characteristics of scattered data
This paper proposed using KDFcmPUM to solve the calibration problem of the orthogonally splitting imaging pose sensor with large scattered data
Summary
In order to achieve pose measurement with a wide range and high precision, the orthogonally splitting imaging pose sensor uses dual linear CCDs (charge-coupled devices) to simulate a single array CCD. The optical structure is specially designed for dual linear CCDs, so the optical structure and assembly structure are more complicated. The pose sensor has various distortions, such as radial distortion caused by a wide field of view, unidirectional distortion caused by a cylindrical mirror, and nonlinear distortion caused by assembly. Distortion correction must be performed before calibration to achieve high precision measurement. Yang [1] used polynomials to solve distortion parameters for distortion correction. The existing calibration method [2,3] cannot satisfy the calibration of the orthogonally splitting imaging pose sensor
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