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Chul-Woo Kang

Bio: Chul-Woo Kang is an academic researcher from Seoul National University. The author has contributed to research in topics: Signal processing & Dead reckoning. The author has an hindex of 2, co-authored 4 publications receiving 24 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, a new Kalman filter method is proposed for roll and pitch attitude estimation in ARS using three gyros and three accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error.
Abstract: To calculate the attitude in ARS(Attitude Reference System) using 3 gyros and 3 accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error. Kalman filter is most popular method to integrate those two sensor outputs. In this paper, new Kalman filtering method is proposed for roll and pitch attitude estimation. New states are defined to make linear equation and algorithm for changing Kalman filter parameters is proposed to ignore disturbances of acceleration. This algorithm can be easily applied to low cost ARS.

18 citations

Journal ArticleDOI
TL;DR: A novel aided navigation method for AUV (Autonomous Underwater Vehicles), where the performance of the reduced 11 order error model is better than that of the conventional 13 ordererror model.
Abstract: Abstract: This paper presents a novel aided navigation method for AUV (Autonomous Underwater Vehicles). The navigation system for AUV includes several sensors such as IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and depth sensor. In general, the 13 order INS error model, which includes depth error, velocity error, attitude error, and the accelerometer and gyroscope biases as state variables is used with measurements from DVL and depth sensors. However, the model may degrade the estimation performance of the heading state. Therefore, the 11 INS error model is proposed. Its validity is verified by using a degree of observability and analyzing steady state error. The performance of the proposed model is shown by the computer simulation. The results show that the performance of the reduced 11 order error model is better than that of the conventional 13 order error model.

3 citations

Journal ArticleDOI
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Abstract: This research have introduced wavelet signal processing technic for improving navigation signals. INS signals can be distorted with conventional pre-filtering method such as low-pass filtering by unwanted smoothing on real signals. But in this paper, wavelet thresholding method is implemented to INS signal to denoise for INS-GPS integrated system. This method reduces signal noise but not distorts the rapid varing signal. And this paper applied thresholding to INS-GPS integrated navigation system and improved navigation performance.

2 citations

01 Jan 2007
TL;DR: An efficient alignment method that is fast and easy to use for the sensor with the arm segment to develop the inertial motion capture system.
Abstract: To develop the inertial motion capture system, the alignment is necessary step to measure the orientation of human arm with inertial sensors. Also it takes long time. In this paper, an efficient alignment method that is fast and easy to use is presented. This paper consists of two parts: the first part is the sensor calibration; and the second part includes an alignment method for the sensor with the arm segment.

1 citations


Cited by
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01 Nov 2004
TL;DR: The design of a modular system for untethered real-time kinematic motion capture using sensors with inertial measuring units (IMU) is described, which is comprised of a set of small and lightweight sensors.
Abstract: We describe the design of a modular system for untethered real-time kinematic motion capture using sensors with inertial measuring units (IMU). Our system is comprised of a set of small and lightweight sensors. Each sensor provides its own global orientation (3 degrees of freedom) and is physically and computationally independent, requiring only external communication. Orientation information from sensors is communicated via wireless to host computer for processing. We present results of the real-time usage of our untethered motion capture system for teleoperating the NASA Robonaut. We also discuss potential applications for untethered motion capture with respect to humanoid robotics.

112 citations

Proceedings ArticleDOI
26 Aug 2009
TL;DR: A Kalman filter model with a modified state is presented and an adaptive algorithm is used to make the filter more robust regarding acceleration disturbances and the performance of the proposed algorithm is shown.
Abstract: This paper introduces the attitude estimation method of humanoid robot using an extended Kalman filter with a fuzzy logic based tuning algorithm. A humanoid robot which uses inertial sensors such as gyros and accelerometers to calculate its attitude is considered. It is known that the attitude update using gyros are prone to diverge and hence the attitude error needs to be compensated using accelerometers. In this paper, a Kalman filter model with a modified state is presented and an adaptive algorithm is used to make the filter more robust regarding acceleration disturbances. If the accelerometer measures any disturbances caused by movement of the vehicle, the characteristics of the filter must be changed to ensure confidence of the outputs of the gyros. The performance of the proposed algorithm is shown by the experiments.

55 citations

Journal ArticleDOI
TL;DR: In this paper, the wavelet denoising techniques using thresholding method are applied to the low cost micro electromechanical system (MEMS)-global positioning system (GPS) integrated system.
Abstract: In this paper, the wavelet denoising techniques using thresholding method are applied to the low cost micro electromechanical system (MEMS)-global positioning system(GPS) integrated system. This was done to improve the navigation performance. The low cost MEMS signals can be distorted with conventional pre-filtering method such as low-pass filtering method. However, wavelet denoising techniques using thresholding method do not distort the rapidly-changing signals. They can reduce the signal noise. This paper verified the improvement of the navigation performance compared to the conventional pre-filtering by simulation and experiment.

24 citations

27 Oct 2010
TL;DR: Wavelet thresholding method is applied to low cost MEMS/GPS integrated navigation system and the improvement of the navigation performance is verified by the experiment.
Abstract: In this paper, wavelet signal processing technique is applied to improving navigation signals. Low cost MEMS signals can be distorted with conventional pre-filtering method such as low-pass filtering which causes unwanted smoothing on real signals. However, wavelet thresholding method does not distort the rapidly-changing signal but reduces signal noise. This paper has applied thresholding method to low cost MEMS/GPS integrated navigation system and verified the improvement of the navigation performance by the experiment.

15 citations

Journal ArticleDOI
민형기, 김지훈, 윤주한, 정은태, 권성하 
TL;DR: In this paper, a complementary filter is used to fuse signals by frequency response of gyroscope and accelerometer in order to measure the inclined angle of balancing robot and linearize that dynamics for using LQR method.
Abstract: This paper shows to stabilize a balancing robot. We derive the dynamics of a balancing robot and design its controller using LQR method. For stabilizing balancing robot, we introduce a method to detect an angle using inertial sensors. In this study, we use a complementary filter to fuse signals by frequency response of gyroscope and accelerometer in order to measure the inclined angle of balancing robot. The filter coefficients are obtained by least square to minimize error in angle-detecting filter design. And then, after we derive a dynamics of balancing robot using Lagrange method, we linearize that dynamics for using LQR method.

11 citations