Search Results (2)

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. Full article

Orthogonally splitting imaging pose sensor is a new sensor with two orthogonal line array charge coupled devices (CCDs). Owing to its special structure, there are distortion correction and imaging model problems during the calibration procedure. This paper proposes a calibration method based on the general imaging model to solve these problems. The method introduces Plücker Coordinate to describe the mapping relation between the image coordinate system and the world coordinate system. This paper solves the mapping relation with radial basis function interpolation and adaptively selecting control points with Kmeans clustering method to improve the fitting accuracy. This paper determines the appropriate radial basis function and its shape parameter by experiments. And these parameters are used to calibrate the orthogonally splitting imaging pose sensor. According to the calibration result, the root mean square (RMS)of calibration dataset and the RMS of test dataset are 0.048 mm and 0.049 mm. A comparative experiment is conducted between the pinhole imaging model and the general imaging model. Experimental results show that the calibration method based on general imaging model applies to the orthogonally splitting imaging pose sensor. The calibration method requires only one image corresponding to the target in the world coordinates and distortion correction is not required to be taken into account. Compared with the calibration method based on the pinhole imaging model, the calibration procedure based on the general imaging model is easier and accuracy is greater. Full article