• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.592-595
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• 2004

This paper presents a study on the development of a multi-sensing inertial sensor with a single mechanical structure, which can be used both as a gyroscope and an accelerometer. The proposed MEMS gyro-accelerometer is designed to detect the angular rate and the acceleration at the same time using two separate detection circuits for one proof mass. In this study, the detection and signal processing circuit for an effective signal processing of different inertial measurements is designed, fabricated, and tested. The experimental results show that the performances of the gyro-accelerometer have resolutions of 1mg and 0.025deg/sec and nonlinearities of less than 0.5% for the accelerometer and the gyroscope, respectively, which are similar results with those of sensors with different structures and different detection circuits. The size of the sensor is reduced almost by 50% comparing with the sensors of separated proof mass.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.873-883
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• 2008

This paper presents a parametric study on the controller design scheme for a gyro-accelerometer to have robust performance under some parameter variations. In particular, an integral and derivative based controller design method is suggested to achieve the desired performances of stability margin, bandwidth, and uniformity of scale for both gyroscopes and accelerometers with uncertainties of quality factor and resonant frequency. The simulation result shows that the control loop based on the suggested method gives satisfactory performance robustness under parameter variations, demonstrating the usefulness of the proposed design scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.82-86
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• 2004

A fuzzy rule-based hand-motion estimation algorithm is proposed for a 6 dimensional spatial tracker in which low cost accelerometers and gyros are employed. To be specific, beginning and stopping of hand motions needs to be accurately detected to initiate and terminate integration process to get position and pose of the hand from accelerometer and gyro signals, since errors due to noise and/or hand-shaking motions accumulated by integration processes. Fuzzy rules of yes or no of hand-motion-detection are here proposed for rules of accelerometer signals, and sum of derivatives of accelerometer and gyro signals. Several experimental results and shown to validate our proposed algorithms.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.3
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• pp.107-117
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• 2019

When a vehicle moves with a high rotation rate, it is not easy to measure the angular velocity using an off-the-shelf gyroscope. If the angular velocity is estimated using the extended Kalman filter in the gyro-free inertial navigation system, the effect of the accelerometer error and initial angular velocity error can be reduced. In this paper, in order to improve the navigation performance of the gyro-free inertial navigation system, an angular velocity estimation method is proposed based on an extended Kalman filter with an accelerometer random bias error model. In order to show the validity of the proposed estimation method, angular velocities and navigation outputs of a vehicle with 3 rev/s rotation rate are estimated. The results are compared with estimates by other methods such as the integration and an extended Kalman filter without an accelerometer random bias error model. The proposed method gives better estimation results than other methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.127-132
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• 2017

In this paper, we propose a controller gain based on model based design and implement the two-wheel inverted pendulum type robot using NXT Lego and RobotC language. Two-wheel inverted pendulum robot consists of NXT mindstorm, servo DC motor with encoder, gyro sensor, and accelerometer sensor. We measurement wheel angle using bulit-in encoder and calculate wheel angle speed using moving average method. Gyro measures body angular velocity and accelerometer measures body pitch angle. We calculate body angle with complementary filter using gyro and accelerometer sensor. The control gain is a weighted value for wheel angle, wheel angular velocity, body pitch angle, and body pich angular velocity, respectively. We experiment and observe the effect of two-wheel inverted pendulum with respect to change of control gains.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.54-58
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• 1989

The purpose of this paper is to develop a more accurate attitude algorithm with low grade gyro output. The proposed algorithm estimates attitudes by combining accelerometer and gyro output. For performance improvement of the algorithm, a method of velocity compensation is proposed for a better attitude estimation which is calculated from the accelerometer output. Velocity compensation is done by using Kalman Filter to estimate another velocity component.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.2
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• pp.91-103
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• 2018

Conventional inertial measurement units cannot be used in the spinning vehicle with high rotation rate due to gyro's narrow operation range. By the way, angular acceleration can be measured using the accelerometer array distributed in the vehicle. This paper derives a mechanization for the gyro-free INS in the navigation frame, and proposes a gyro-free INS algorithm based on the derived mechanization. In addition, the proposed algorithm is used to estimate angular velocity, attitude, velocity, and position of a spinning vehicle with high rotation rate. A MATLAB-based software platform is configured in order to show validation of the proposed algorithm. The reference trajectory of a spinning vehicle at 3 round per second, 30 round per second are set up, and the outputs of accelerometer are generated when triads of accelerometer are located at the origin and all the axes. Navigation results of the proposed algorithm for the generated output are presented. The results show that the proposed navigation algorithm can be applied to the spinning vehicle with high rotation rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.285-293
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• 2017

Jump rope has two motions. It starts as hand motion and ends as jump motion. Therefore, two motions should be considered together to detect rotations accurately. But previous researches only consider one of the two motions as in push-up, sit-up, lift dumbbells etc, which results in inaccurate detection of rotations. In this paper, detection of rotation in jump rope using two motions through 6-axis accelerometer gyro sensor is proposed. Jump motion is detected using accelerometer sensor and hand motion is detected using gyro sensor. Also start point and end point of jump rope is detected using magnitude and standard deviation of accelerometer and gyro sensor values. The count of rotation is detected using y-axis of gyro sensor value. Y-axis of gyro sensor value indicate hand motion of jump rope motion. The usefulness of the proposed method is confirmed through experimental results.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.334-343
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• 2014

In this paper, we suggest a method to improve the fusion of an accelerometer and gyro sensor by using a Kalman filter to produce a more high-quality respiration signal to supplement the weakness of using a single accelerometer. To evaluate our proposed algorithm's performance, we developed a chest belt-type module. We performed experiments consisting of aerobic exercise and muscular exercises with 10 subjects. We compared the derived respiration signal from the accelerometer with that from our algorithm using the standard respiration signal from the piezoelectric sensor in the time and frequency domains during the aerobic and muscular exercises. We also analyzed the time delay to verify the synchronization between the output and standard signals. We confirmed that our algorithm improved the respiratory rate's detection accuracy by 4.6% and 9.54% for the treadmill and leg press, respectively, which are dynamic. We also confirmed a small time delay of about 0.638 s on average. We determined that real-time monitoring of the respiration signal is possible. In conclusion, our suggested algorithm can acquire a more high-quality respiration signal in a dynamic exercise environment away from a limited static environment to provide safer and more effective exercises and improve exercise sustainability.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.674-679
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• 1998

In this paper, a new coarse alignment algorithm is proposed for roughly determining the initial attitude of the vehicle. The algorithm, referred as two-step coarse alignment algorithm, computes roll and pitch angle of the vehicle using accelerometer outputs, and then determines yaw angle with gyro outputs. With the geometric relation between sensor outputs and attitude angles, the algorithm error is analytically derived and compared with the previous coarse alignment algorithm that computes a transformation matrix using accelerometer md gyro outputs simultaneously. The simulation is also performed by varying the sensor errors. The results show that the proposed two-step coarse alignment algorithm has better performance for east tilt angle.