Reference Filtering Research Articles

Generalization of reference filtering control strategy for 2D/3D visual feedback control of industrial robot manipulators

ABSTRACT This paper develops the application of the Dual Rate Dual Sampling Reference Filtering Control Strategy to 2D and 3D visual feedback control. This strategy allows to overcome the problem of sensor latency and to address the problem of control task failure due to visual features leaving the camera field of view. In particular, a Dual Rate Kalman Filter is used to generate inter-sample estimations of the visual features to deal with the problem of vision sensor latency, whereas a Dual Rate Extended Kalman Filter Smoother is used to generate more convenient visual features trajectories in the image plane. Both 2D and 3D visual feedback control approaches are widely analyzed throughout the paper, as well as the overall system performance using different visual feedback controllers, providing a set of results that highlight the improvements in terms of solution reachability, robustness, and time domain response. The proposed control strategy has been validated on an industrial system with hard real-time limitations, consisting of a 6 DOF industrial manipulator, a 5 MP camera, and a PLC as controller.

3D profile filter algorithm based on parallel generalized B-spline approximating Gaussian

Currently, the approximation methods of the Gaussian filter by some other spline filters have been developed. However, these methods are only suitable for the study of one-dimensional filtering, when these methods are used for three-dimensional filtering, it is found that a rounding error and quantization error would be passed to the next in every part. In this paper, a new and high-precision implementation approach for Gaussian filter is described, which is suitable for three-dimensional reference filtering. Based on the theory of generalized B-spline function and the variational principle, the transmission characteristics of a digital filter can be changed through the sensitivity of the parameters (t1, t2), and which can also reduce the rounding error and quantization error by the filter in a parallel form instead of the cascade form. Finally, the approximation filter of Gaussian filter is obtained. In order to verify the feasibility of the new algorithm, the reference extraction of the conventional methods are also used and compared. The experiments are conducted on the measured optical surface, and the results show that the total calculation by the new algorithm only requires 0.07 s for 480×480 data points; the amplitude deviation between the reference of the parallel form filter and the Gaussian filter is smaller; the new method is closer to the characteristic of the Gaussian filter through the analysis of three-dimensional roughness parameters, comparing with the cascade generalized B-spline approximating Gaussian. So the new algorithm is also efficient and accurate for the implementation of Gaussian filter in the application of surface roughness measurement.

Sampling and processing for compressive holography [Invited

Compressive holography applies sparsity priors to data acquired by digital holography to infer a small number of object features or basis vectors from a slightly larger number of discrete measurements. Compressive holography may be applied to reconstruct three-dimensional (3D) images from two-dimensional (2D) measurements or to reconstruct 2D images from sparse apertures. This paper is a tutorial covering practical compressive holography procedures, including field propagation, reference filtering, and inverse problems in compressive holography. We present as examples 3D tomography from a 2D hologram, 2D image reconstruction from a sparse aperture, and diffuse object estimation from diverse speckle realizations.

Statistical Evaluation of Adaptive Threshold Alignment for a Multi-Carrier CDMA Code Synchronization

Summary This letter presents a statistical analysis of the decision threshold for a multi-carrier (MC) DS/CDMA acquisition system with a reference filter. The probabilities of detection and false alarm are derived, and the mean acquisition time is evaluated as a measure of the system performance. From the results, it is shown that in the performance analysis of the hybrid acquisition system with reference filtering, the statistical evaluation of the decision threshold seems more appropriate than the approximation of the decision threshold adopted in other schemes [7,8].

Detection Technique for Direct-Sequence Spread-Spectrum Parallel Acquisition in a Nonselective Rician Fading Channel

This paper presents a statistical analysis of the decision threshold for direct-sequence spread-spectrum (DS-SS) parallel Pseuda-Naise (PN) cade acquisitian with a reference filter. The probabilities of detectian and false alarm are derived, and the mean acquisitian time is evaluated as a measure of the system performance in both nonfading and Rician fading channels. Fram the statistical results, it is shown that in the performance analysis of the parallel acquisition system with reference filtering, the statistical evaluatian of the decision threshold seems more appropriate than the approximation of the decision threshold adopted in other schemes [4,5]. It is also shown that the parallel acquisition scheme provides a suboptimal threshold value for a wide range of SNR such that the mean acquisition time is minimized.

Statistical analysis of decision threshold for parallelacquisition with reference filtering in Rician fadingchannel

Statistical analysis of the decision threshold for parallel PN code acquisition in a Rician fading channel is presented. It is shown that in the performance analysis of the acquisition system with reference filtering , the statistical evaluation of the decision threshold seems more appropriate than the approximation of the decision threshold.