• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.342-351
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• 2010

UAV (Unmanned Aerial Vehicle) have an INS(Inertial Navigation System) equipment and also have an electro-optical Equipment for mission. This paper proposes the vision based attitude estimation algorithm using Kalman Filter and Optical flow for UAV. Optical flow is acquired from the movie of camera which is equipped on UAV and UAV's attitude is measured from optical flow. In this paper, Kalman Filter has been used for the settlement of the low reliability and estimation of UAV's attitude. Algorithm verification was performed through experiments. The experiment has been used rate table and real flight video. Then, this paper shows the verification result of UAV's attitude estimation algorithm. When the rate table was tested, the error was in 2 degree and the tendency was similar with AHRS measurement states. However, on the experiment of real flight movie, maximum yaw error was 21 degree and Maximum pitch error was 7.8 degree.

• Journal of Ship and Ocean Technology
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• v.3 no.3
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• pp.25-44
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• 1999

Estimation efficiencies according to different sea trial are investigated in connection with sensitivity analysis, and new trial method is proposed which can improve the estimation efficiency of hydrodynamic derivatives. MMG Equation with Kijima's formula is used for simulation. Extended Kalman Filter is chosen for estimation technique and hydrodynamic derivatives of interest is limited to 12 of those in sway and yaw equations. Esso Osaka is selected for the test ship. Sensitivity analysis and estimation results based on conventional trials show that a more sensitive derivative gives more efficient estimation result. Sensitivities of nonlinear derivatives become pronounced in the trial where steady condition lasts longer such as turning test, while sensitivities of linear derivatives gas a larger values in the trial where unsteady condition lasts longer such as 10deg-10deg zigzag test. Consequently, in new method , named S-type trial, steady and unsteady condition are combined appropriately to increase sensitivities. Linear derivatives are estimated better in S-type trial and the estimation of nonlinear derivatives is improved to extent.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.5
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• pp.523-529
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• 2008

The course stability performance for tankers is evaluated by computational fluid dynamics. In the present work, a Reynolds averaged Navier-Stokes (RANS) code is applied to a maneuvering problem covering the pure drift and yaw motions. The purposes of this study are to evaluate the hydrodynamic force in the bare hull (AFRAMAX) in pure drift and yaw motion and to provide information about the trends in the forces and moments when the rudder angles are varied. The flow simulation is performed by FLUENT. The CFD code is examined to find the optimistic computational condition such as size of grid, turbulence model and initial condition. The hydrodynamic derivatives in drift and pure yaw motion are estimated by the numerical simulation, and then the stability levers are calculated. It is confirmed that the computations show the superiority and inferiority of course stability performance according to the hull forms. Finally, the CFD code is applied to the estimation of the rudder forces when the rudder angles are varied. The propeller effect expressed by the body force distribution is also included.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.101-110
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• 2018

This paper introduces feedback linearization (FL) based adaptive sliding mode control (ASMC) effective against ground effects of the quadrotor UAV. The proposed control has the capability of estimation and effective rejection of those effects by adaptive mechanism, which resulting stable attitude and positioning of the quadrotor. As output variables of quadrotor, x-y-z position and yaw angle are chosen. Dynamic extension of the quadrotor dynamics is obtained for terms of roll and pitch control input to be appeared explicitly in x-y-z dynamics, and then linear feedback control including a ground effect is designed. A sliding mode control (SMC) is designed with a class of FL including higher derivative terms, sliding surfaces for which is designed as a class of integral type of resulting closed loop dynamics. The asymptotic stability of the overall system was assured, based on Lyapunov stability methods. It was evaluated through some simulation that attitude control capability is stable under excessive estimation error for unknown ground effect and initial attitude of roll, pitch, and yaw angle of $30^{\circ}$ in all. Effectiveness of the proposed method was shown for quadrotor system with ground effects.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.470-476
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• 2016

This paper proposes a practical algorithm for the reduction of measurement errors due to drift in a micro-electromechanical system (MEMS) gyros that are used for a mobile robot. Any drift in a MEMS gyro will cause an unbounded growth of errors in the estimation of heading, which makes it nearly useless in applications that require high accuracy over a long operating time. In proposed method, maneuvers of a cleaning robot are observed through encoders' measurement process and a decision to correct bias drift will be made if necessary. The method used in this paper is called the "heading estimation filter". To evaluate the accuracy of the proposed method, a comparison was made between the estimation of the heading of the cleaning robot and one from a motion capture system.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.575-582
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• 2019

Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.942-956
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• 2014

This paper proposes a real-time hand pose tracking method using a monocular RGB camera. Hand tracking has high ambiguity since a hand has a number of degrees of freedom. Thus, to reduce the ambiguity the proposed method adopts the step-by-step estimation scheme: a palm pose estimation, a finger yaw motion estimation, and a finger pitch motion estimation, which are performed in consecutive order. Assuming a hand to be a plane, the proposed method utilizes a planar hand model, which facilitates a hand model regeneration. The hand model regeneration modifies the hand model to fit a current user's hand, and improves robustness and accuracy of the tracking results. The proposed method can work in real-time and does not require GPU-based processing. Thus, it can be applied to various platforms including mobile devices such as Google Glass. The effectiveness and performance of the proposed method will be verified through various experiments.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.50-58
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• 2006

Free running model tests gives us only maneuvering indices not hydrodynamic derivatives. For this reason, system identification method has been applied to the measured data to identify mathematical model describing hydrodynamic force. However It is difficult to obtain complete set of maneuvering derivatives because of strong correlation of sway velocity and yaw rate. Therefore, in this paper, we assumed that sway velocity related coefficients would be obtained by oblique towing test. and then proposed new procedure to estimate yaw related coefficients. To do this, correlation and regression analyses were carried out to establish modified model and estimate maneuvering derivatives. Also D-optimal rudder input scenario was found based on the modified model and confirmed the validity of its sufficient richness as a input scenario.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1441-1461
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• 2017

Nowadays, Dynamic Adaptive Streaming over HTTP (DASH) has become very popular in streaming multimedia contents. In DASH, a client estimates current network bandwidth and then determines an appropriate video quality with bitrate matching the estimated bandwidth. Thus, estimating accurately the available bandwidth is a significant premise in the quality of video streaming, especially when network traffic fluctuates substantially. To cope with this challenge, researchers have presented various filters to estimate network bandwidth adaptively. However, experiment results show that current schemes either adapt slowly to network changes or adapt fast but are very sensitive to delay jitter and produce sharply changed estimation. This paper presents a novel bandwidth estimation scheme based on Moving Average Convergence Divergence (MACD). We applied an MACD indicator and its two thresholds to classifying network states into stable state and agile state, based on the network state different filters are applied to estimate network bandwidth. In the paper, we studied the performance of various MACD indicators and the threshold values on bandwidth estimation. Then we used a DASH proxy-based environment to compare the performance of the presented scheme with current well-known schemes. The simulation results illustrate that the MACD-based bandwidth estimation scheme performs superior to existing schemes both in the speed of adaptively to network changes and in stability in bandwidth estimation.