• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1167-1175
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• 2010

This paper presents the use of the inertial measurement unit information and the infrared sector information for getting the position of an object. Travel distance is usually calculated from the double integration of the accelerometer output with respect to time; however, the accumulated errors due to the drift are inevitable. The orientation change of the accelerometer also causes error because the gravity is added to the measured acceleration. Unless three axis orientations are completely identified, the accelerometer alone does not provide correct acceleration for estimating the travel distance. We propose a way of minimizing the error due to the change of the orientation. In order to reduce the accumulated error, the infrared sector information is fused with the inertial measurement unit information. Infrared sector information has highly deterministic characteristics, different from RFID. By putting several infrared emitters on the ceiling, the floor is divided into many different sectors and each sector is set to have a unique identification. Infrared light based sector information tells the sector the object is in, but the size of the uncertainty is too large if only the sector information is used. This paper presents an algorithm which combines both the inertial measurement unit information and the sector information so that the size of the uncertainty becomes smaller. It also introduces a framework which can be used with other types of the artificial landmarks. The characteristics of the developed infrared light based sector and the proposed algorithm are verified from the experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.799-807
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• 2017

In this paper, a new method is proposed for estimating pedestrians' walking velocity based on lower-limb kinematics and wearable inertial measurement unit (IMU) sensors. While the soles and ground are not in contact during the walking cycle, the walking velocity can be estimated by integrating the acceleration output of the inertial sensor mounted on the pelvis. To minimize the effects of acceleration measurement errors caused by the tilt of the pelvis while walking, the estimated walking velocity based on lower-limb kinematics is imposed as the initial value in the acceleration signal integration process of the pelvis inertial sensor. In the experiment involving outdoor walking for six minutes, sensor drift due to error accumulation was not observed, and the RMS error in the walking velocity estimation was less than 0.08 m/s.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.75-82
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• 2004

A metrological atomic force microscope (M-AFM) was developed fur the length measurements of nanometer range, through the modification of a commercial AFM. To eliminate nonlinearity and crosstalk of the PZT tube scanner of the commercial AFM, a two-axis flexure hinge scanner employing built-in capacitive sensors is used for X-Y motion instead of PZT tube scanner. Then two-dimensional displacement of the scanner is measured using two-axis heterodyne laser interferometer to ensure the meter-traceability. Through the measurements of several specimens, we could verify the elimination of nonlinearity and crosstalk. The uncertainty of length measurements was estimated according to the Guide to the Expression of Uncertainty in Measurement. Among several sources of uncertainty, the primary one is the drift of laser interferometer output, which occurs mainly from the variation of refractive index of air and the thermal stability. The Abbe error, which is proportional to the measured length, is another primary uncertainty source coming from the parasitic motion of the scanner. The expanded uncertainty (k =2) of length measurements using the M-AFM is √(4.26)$^2$+(2.84${\times}$10$^{-4}$ ${\times}$L)$^2$(nm), where f is the measured length in nm. We also measured the pitch of one-dimensional grating and compared the results with those obtained by optical diffractometry. The relative difference between these results is less than 0.01 %.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.389-395
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• 2021

In this paper, we propose a target image exchange model to improve performance of the object tracking algorithm based on a Siamese network. The object tracking algorithm based on the Siamese network tracks the object by finding the most similar part in the search image using only the target image specified in the first frame of the sequence. Since only the object of the first frame and the search image compare similarity, if tracking fails once, errors accumulate and drift in a part other than the tracked object occurs. Therefore, by designing a CNN(Convolutional Neural Network) based model, we check whether the tracking is progressing well, and the target image exchange timing is defined by using the score output from the Siamese network-based object tracking algorithm. The proposed model is evaluated the performance using the VOT-2018 dataset, and finally achieved an accuracy of 0.611 and a robustness of 22.816.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.2
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• pp.1-8
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• 2012

This paper presents the accelerometer which is a key component of TPMS(Tire Pressure Monitoring System). Generally a piezoresistive accelerometer has characteristics of lower cost, better linearity and better immunity about the environmnet noise than a capacitive one. Three types of piezoresistive accelerometers are degined and simulated using ANSYS program. The best one is a piezoresistive sensor which is supported by four beams located at the center of the edge of the mass after comparing the characteristics of resonant frequency of the three types. Considering the sensor size and a simulated maximum stress and maximum displacement, the length of beams is set as $200{\mu}m$. The size of a piezoresistive accelerometer is $3.0mm{\times}3.0mm{\times}0.4mm$. The sensor output is characterized by measuring the output characteristic depending on angle. As a result the offset voltage of the accelerometer is 43.2 mV and its sensitivity is $42.5{\mu}V/V/g$. The temperature bias drift is measured. The shock durability of the sensor is 1500g and the measuring range is 0 ~ 60 g.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.167-176
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• 2022

We designed a borehole deviation survey tool applicable for steel-cased holes, K-DEV, and developed a prototype for a depth of 500 m aiming to development of own equipment required to secure deep subsurface characterization technologies. K-DEV is equipped with sensors that provide digital output with verified high performance; moreover, it is also compatible with logging winch systems used in Korea. The K-DEV prototype has a nonmagnetic stainless steel housing with an outer diameter of 48.3 mm, which has been tested in the laboratory for water resistance up to 20 MPa and for durability by running into a 1-km deep borehole. We confirmed the operational stability and data repeatability of the prototype by constantly logging up and down to the depth of 600 m. A high-precision micro-electro-mechanical system (MEMS) gyroscope was used for the K-DEV prototype as the gyro sensor, which is crucial for azimuth determination in cased holes. Additionally, we devised an accurate trajectory survey algorithm by employing Unscented Kalman filtering and data fusion for optimization. The borehole test with K-DEV and a commercial logging tool produced sufficiently similar results. Furthermore, the issue of error accumulation due to drift over time of the MEMS gyro was successfully overcome by compensating with stationary measurements for the same attitude at the wellhead before and after logging, as demonstrated by the nearly identical result to the open hole. We believe that the methodology of K-DEV development and operational stability, as well as the data reliability of the prototype, were confirmed through these test applications.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.10-20
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• 2007

For spacecraft attitude control, reaction wheel (RW) steering laws with more than three wheels for three-axis attitude control can be derived by using a control allocation (CA) approach.1-2 The CA technique deals with a problem of distributing a given control demand to available sets of actuators.3-4 There are many references for CA with applications to aerospace systems. For spacecraft, the control torque command for three body-fixed reference frames can be constructed by a combination of multiple wheels, usually four-wheel pyramid sets. Multi-wheel configurations can be exploited to satisfy a body-axis control torque requirement while satisfying objectives such as minimum control energy.1-2 In general, the reaction wheel steering laws determine required torque command for each wheel in the form of matrix pseudo-inverse. In general, the attitude control command is generated in the form of a feedback control. The spacecraft body angular rate measured by gyros is used to estimate angular displacement also.⁵ Combination of the body angular rate and attitude parameters such as quaternion and MRPs(Modified Rodrigues Parameters) is typically used in synthesizing the control command which should be produced by RWs.¹ The attitude sensor signals are usually corrupted by noise; gyros tend to contain errors such as drift and random noise. The attitude determination system can estimate such errors, and provide best true signals for feedback control.⁶ Even if the attitude determination system, for instance, sophisticated algorithm such as the EKF(Extended Kalman Filter) algorithm⁶, can eliminate the errors efficiently, it is quite probable that the control command still contains noise sources. The noise and/or other high frequency components in the control command would cause the wheel speed to change in an undesirable manner. The closed-loop system, governed by the feedback control law, is also directly affected by the noise due to imperfect sensor characteristics. The noise components in the sensor signal should be mitigated so that the control command is isolated from the noise effect. This can be done by adding a filter to the sensor output or preventing rapid change in the control command. Dynamic control allocation(DCA), recently studied by Härkegård, is to distribute the control command in the sense of dynamics⁴: the allocation is made over a certain time interval, not a fixed time instant. The dynamic behavior of the control command is taken into account in the course of distributing the control command. Not only the control command requirement, but also variation of the control command over a sampling interval is included in the performance criterion to be optimized. The result is a control command in the form of a finite difference equation over the given time interval.⁴ It results in a filter dynamics by taking the previous control command into account for the synthesis of current control command. Stability of the proposed dynamic control allocation (CA) approach was proved to ensure the control command is bounded at the steady-state. In this study, we extended the results presented in Ref. 4 by adding a two-step dynamic CA term in deriving the control allocation law. Also, the strict equality constraint, between the virtual and actual control inputs, is relaxed in order to construct control command with a smooth profile. The proposed DCA technique is applied to a spacecraft attitude control problem. The sensor noise and/or irregular signals, which are existent in most of spacecraft attitude sensors, can be handled effectively by the proposed approach.