SUMMARYExisting measurement equipments easily determine position with high precision. However, they evaluate orientation with low precision. It is necessary to minimize the effect of measurement error on identification accuracy. In this study, a method for kinematic calibration based on the product of exponentials (POE) is presented to improve the absolute positioning accuracy of a sliding manipulator. An error model with uniform and generic modeling rules is established in which the tool frame is selected as the reference frame. Furthermore, the redundant parameters of the error model are removed. Subsequently, the actual kinematic parameters are identified by using the least square method. Finally, the process of the improved method is discussed. Kinematic calibration simulations of a sliding manipulator are implemented. The results indicate that the proposed method significantly improves the precision of the sliding manipulator. The improved POE kinematic calibration method offers convenience, efficiency, and high precision. The proposed method can be applied to all types of serial robots with n-DOF
Doppler asymmetric spatial heterodyne spectroscopy is recently developed for spaceborne measurement of middle and upper atmospheric wind field, which relies on the accurate inverse of interferogram phase to calculate the Doppler shift of airglow emission lines. The change of temperature leads to thermal deformation of the optical and mechanical components, causing thermal drift of the imaging plane relative to detector, changing the distribution of interferogram phase on pixels, and directly introducing phase errors to affect the wind speed inversion. In order to reduce the influence of imaging thermal drift on phase inversion, this paper uses the segmented fitting method to detect the sub-pixel edges of notch patterns and monitor imaging thermal drift accordingly. In the thermal stability test of a near-infrared Doppler asymmetric spatial heterodyne interferometer prototype, the thermal imaging drifts and ambient temperature showed a high consistency in the trend of high-frequency oscillation, and the correlation coefficient can reach 0.86 after removing the baseline. After phase correct using the thermal imaging shift, the high-frequency oscillation of interferogram phase shift is also greatly suppressed. In order to further verify the accuracy of the algorithm, the influence of the data signal-to-noise ratio and the data distribution characteristic parameter errors used in the fitting on the edge detection was simulated. The results show that the edge detection accuracy is mainly restricted by the data signal-to-noise ratio and the accuracy of the fringe frequency parameters. When the error of the fringe frequency parameter used for fitting is less than 0.5%, the error of other data distribution characteristic parameters is less than 5%, and the data signal-to-noise ratio is more than 35 times, the algorithm in this paper can achieve a detection accuracy higher than 0.05 pixels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.