• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.518-522
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• 2001

The main problem of the calibration of robots is to measure the position and orientation of a robot end effector. The calibration methods can be used as tool to improve the accuracy of robots without change of the arm or control architecture or robots. But such calibration methods require accurate measurements. Dynamic measurement of position and orientation provides a solution for this problem and improves dynamic accuracy by dynamic calibration of robots. This paper describes the development of the laser tracking system capable of determining the static and dynamic performance of industrial robots. The structure and systems components are presented and basic experimental results are included to demonstrated the instrument performance. The system can be applied to the remote controlled mobile robots as well s the calibration of robots.

• Geomechanics and Engineering
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• v.2 no.3
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• pp.177-190
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• 2010

This paper presents the details of indigenous development of the piezovibrocone and calibration chamber. The developed cone has a cylindrical friction sleeve of $150cm^2$ surface area, capped with a $60^{\circ}$ apex angle conical tip of $15cm^2$ cross sectional area. It has a hydraulic shaker, coupled to the cone penetrometer with a linear displacement unit. The hydraulic shaker can produce cyclic load in different types of wave forms (sine, Hover sine, triangular, rectangular and external wave) at a range of frequency 1-10 Hz with maximum amplitude of 10 cm. The piezovibrocone can be driven at the standard rate of 2 cm/sec using a loading unit of 10 ton capacity. The calibration chamber is of size $2m{\times}2m{\times}2m$. The sides of the chamber and the top as well as the bottom portions are rigid. It has a provision to apply confining pressure (to a maximum value of $4kg/cm^2$) through the flexible rubber membrane inlined with the side walls of the calibration chamber. The preliminary static as well as dynamic cone penetration tests have been done sand in the calibration chamber. From the experimental results, an attempt has been made to classify the soil based on friction ratio ($f_R$) and the cone tip resistance ($q_c$).

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.77-84
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• 2013

Most research on the inkjet printing technology has focused on the development of inkjet head itself, and of process, not on the landing accuracy of the droplets to a target. Thus, this paper presents the modeling and experimental verification on the static landing accuracy and precision of the droplets from the magnetostrictive inkjet head. A simple model based on the angle deviation of a nozzle tip and on a distance to a substrate is considered, assuming that there is no ambient effect. The angle deviation of the nozzle tip is determined by using its digital image with the aid of a pixel calculation program, and the distance to the substrate is set to 1 mm. Three experiments have planned and preformed. The first experiment is to collect the initial data for the landing distribution of the droplets. The second experiment is to collect the repeatability data of the stage used. Then, these data are used to rederive the equation for the final landing position of the droplet. The final experiment is to verify the equation and to show the calibration results. The respective landing accuracy of the droplet after calibration on the x-axis and on y axis has improved from $338.51{\mu}m$ and $-133.63{\mu}m$ to $7.06{\mu}m$ and $13.11{\mu}m$. The respective percent improvement on the x-axis and on y axis reaches about 98 and about 90. The respective landing precision of the droplet after calibration on the x-axis and on y axis has improved from ${\pm}182.6{\mu}m$ and ${\pm}182.88{\mu}m$ to ${\pm}24.64{\mu}m$ and ${\pm}42.76{\mu}m$. The respective percent improvement on the x-axis and on y axis reaches about 87 and about 77.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.43-51
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• 2009

In the flight of air vehicles, accurate air data information is required to control them effectively. Especially, helicopters are often put in drastic motion involved with high angle of attacks in order to perform difficult missions. Among various sensors, the multi function probe (MFP) has been used in the present study mainly owing to its advantages in structural simplicity and capability of providing various information such as static and total pressure, speed, and pitch and yaw angles. In this study, a five-hole multi-function probe (FHMFP) is developed and its calibration is conducted using multiple regressions. In this work a calibration study on the FHMFP, an air data sensor for helicopters, is reported. It is shown that the pitch and yaw angles' accuracy of calibration is ${\pm}0.91^{\circ}$ at a cone angle of $0^{\circ}{\sim}30^{\circ}$ and ${\pm}2.0^{\circ}$ at $30^{\circ}{\sim}43^{\circ}$, respectively, which is summarized in table 3.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.814-822
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• 2022

The deployment of sensors for Structural Health Monitoring requires a complicated network arrangement, ground truthing, and calibration for validating sensor performance periodically. Any conventional sensor on a structural element is also subjected to static and dynamic vertical loadings in conjunction with other environmental factors, such as brightness, noise, temperature, and humidity. A structural model with strain gauges was built and tested to get realistic sensory information. This paper investigates different deep learning architectures and algorithms, including unsupervised, autoencoder, and supervised methods, to benchmark blind drift calibration methods using deep learning. It involves a fully connected neural network (FCNN), a long short-term memory (LSTM), and a gated recurrent unit (GRU) to address the blind drift calibration problem (i.e., performing calibrations of installed sensors when ground truth is not available). The results show that the supervised methods perform much better than unsupervised methods, such as an autoencoder, when ground truths are available. Furthermore, taking advantage of time-series information, the GRU model generates the most precise predictions to remove the drift overall.

• Proceedings of the KAIS Fall Conference
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• 2004.11a
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• pp.234-239
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• 2004

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process fur each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.63-70
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• 1994

This paper presents manufacturing and evaluation of a non-contact rotational torque measurement system which consists of torque cell, telemeter system, transmitter and receiver coil, transmitter, receiver and telemeter indicator. Static calibration test results show that the system has a maximum uncertaintry of 05% or less. A standar calibration system for rotational torque is used to evaluate the measurement system, As a result, the maximum uncertainty for measuring rotational torque by this system is 2% or less. We may conclude that the measurement system is sufficient to measure rotational torque of shaft in industry.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.30-32
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• 2004

With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. The first establishes reference points in space, and the second uses a grid type frame and statistical method. But, the former has difficulty to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. It can easily estimate camera calibration parameters such as lens distortion, focal length, scale factor, pose, orientations, and distance. The advantage of this algorithm is that it can estimate the distance of the object. Also, the proposed camera calibration method is possible estimate distance in dynamic environment such as autonomous navigation. To validate proposed method, we set up the experiments with a frame on rotator at a distance of 1, 2, 3, 4[m] from camera and rotate the frame from -60 to 60 degrees. Both computer simulation and real data have been used to test the proposed method and very good results have been obtained. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. The average scale factor tends to fluctuate with small variation and makes distance error decrease. Compared with classical methods that use stereo camera or two or three orthogonal planes, the proposed method is easy to use and flexible. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.1
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• pp.27-38
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• 2002

The effects of Reynolds number on the non-nulling calibrations of a cone-type ave-type probe in low-speed flows have been investigated at Reynolds numbers of 2.04$\times$10$^3$, 4.09$\times$10$^3$and 6.13$\times$10$^3$. The calibration is conducted at the pitch and yaw angles in ranges between -35 degrees and 35 degrees with an angle interval of 5 degrees. In addition to the calibration coefficients, reduced pitch and yaw angles, static and total pressures, and velocity magnitude are obtained through a typical non-nulling reduction procedure. The result shows that each calibration coefficient, in general, is a function of both the pitch and yaw angles, so that the pre-existing calibration data in a nulling mode are not enough in accounting far the full non-nulling calibration characteristics. Due to interference of the probe stem, the calibration coefficient are more sensitive to Reynolds number at positive pitch angles than at negative ones. The calibration data reduced in this study may serve as a guide line in the estimation of uncertainty intervals resulted from the Reynolds number effects at low Reynolds numbers.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2372-2374
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• 2003

With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. The first establishes reference points in space, and the second uses a grid type frame and statistical method. But, the former has difficulty to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. It can easily estimate camera calibration parameters such as focal length, scale factor, pose, orientations, and distance. But, radial lens distortion is not modeled. The advantage of this algorithm is that it can estimate the distance of the object. Also, the proposed camera calibration method is possible estimate distance in dynamic environment such as autonomous navigation. To validate proposed method, we set up the experiments with a frame on rotator at a distance of 1,2,3,4[m] from camera and rotate the frame from -60 to 60 degrees. Both computer simulation and real data have been used to test the proposed method and very good results have been obtained. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use.