• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.9
• /
• pp.208-214
• /
• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• Journal of the Society of Naval Architects of Korea
• /
• v.38 no.4
• /
• pp.30-38
• /
• 2001

The current is considered in the conventional manoeuvering equation. This equation is represented as the nonlinear state and measurement equations in which external forces and the direction and the velocity of current are augmented as that variables. The external forces are modeled as the third-order Gauss-Markov processes and the direction and the velocity of current are assumed to be constant. The augmented state variables are estimated with extended Kalman-Bucy filter and the fixed-interval smoother. While Hwang estimated motion state variables, hydrodynamic coefficients and the current variables simultaneously by using extended Kalman filter, external forces of surge, sway and yaw and the direction and the velocity of current are the only parameters to be estimated in the estimation-before-modeling method. The current variables are satisfactorily estimated in simulation process where the measurement noise is present.

• Journal of Convergence for Information Technology
• /
• v.8 no.6
• /
• pp.135-142
• /
• 2018

In recent years, researches utilizing UAV for military purposes such as precision tracking and batting have been actively conducted. In order to track the preceding flight, there has been a previous research on estimating the attitude information of the flight such as roll, pitch, and yaw using images taken from the rear UAV. In this study, we propose a method to estimate the attitude information more precisely by applying the Kalman filter to the existing image processing technique. By applying the Kalman filter to the estimated attitude data using image processing, we could reduce the estimation error of the attitude angle significantly. Through the simulation experiments, it was confirmed that the estimation using the Kalman filter can estimate the posture information of the aircraft more accurately.

• Journal of Convergence for Information Technology
• /
• v.7 no.5
• /
• pp.137-148
• /
• 2017

Recently, researchers are actively addressed to utilize Unmanned Aerial Vehicles(UAV) for military and industry applications. One of these applications is to trace the preceding flight when it is necessary to track the route of the suspicious reconnaissance aircraft in secret, and it is necessary to estimate the attitude of the target flight such as Roll, Yaw, and Pitch angles in each instant. In this paper, we propose a method for estimating in real time the attitude of a target aircraft using the video information that is provide by an external camera of a following aircraft. Various image processing methods such as color space division, template matching, and statistical methods such as linear regression were applied to detect and estimate key points and Euler angles. As a result of comparing the X-plane flight data with the estimated flight data through the simulation experiment, it is shown that the proposed method can be an effective method to estimate the flight attitude information of the previous flight.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.762-766
• /
• 2003

In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.1103-1108
• /
• 2007

This paper describes a robust model-based roll state estimator for application to the detection of impending vehicle rollover. The roll state estimator is based on a 2-D bicycle model and a roll model to estimate the maneuver-induced vehicle roll motion. The measurement signals are lateral acceleration, yaw rate, steering angle, and vehicle speed. Vehicle mass is adapted to obtain robust performance of the estimator. Computer simulation is conducted to evaluate the proposed roll state estimator by using a validated vehicle simulator. It is shown that the roll state estimator shows robust performance without exact vehicle mass information.

• Annual Conference of KIPS
• /
• 2019.10a
• /
• pp.660-663
• /
• 2019

본 논문은 진공을 이용한 흡착방식과 바퀴형 이동방식을 사용하는 벽면이동로봇의 균열 위치 추정에 관한 연구로써, 로봇의 Yaw값에 대해 PID제어를 통해 로봇의 방향을 제어 하고 이를 바탕으로 엔코더 모터의 홀센서와 IMU를 기반으로 하여 균열 위치를 추정 한다. 위치 추정 성능을 검증하기 위해 실제 위치와 추정된 위치를 비교하고 결과를 제시하였다.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.4
• /
• pp.53-59
• /
• 2022

This paper describes an integrated control of torque vectoring and rear wheel steering using model predictive control. The control objective is to minimize the yaw rate and body side slip angle errors with chattering alleviation. The proposed model predictive controller is devised using a linear parameter-varying (LPV) vehicle model with real time estimation of the varying model parameters. The proposed controller has been investigated via computer simulations. In the simulation results, the performance of the proposed controller has been compared with uncontrolled cases. The simulation results show that the proposed algorithm can improve the lateral stability and handling performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.2
• /
• pp.131-142
• /
• 2015

In order to support the development of a cost-effective river bathymetric system, this research has focused on modeling GPS observables, which are obtained by array of five single-frequency receivers (i.e., two references and three rovers) to estimate the high accurate kinematic position, and the surveying vessel altitude. Also, by applying all GPS measurements as multiple-baselines with constraining rover baselines, we derived the socalled ‘kinematic network model.’ From the model, the integer-constrained least-squares (LS) for position estimation and the implicit LS for attitude determination were implemented, while a series of simulation tests with respect to the baseline lengths around 2km performed to demonstrate its accuracy analysis. The on-the-fly (OTF) ambiguity resolution tests revealed that ninety-nine percents of time-to-fix-first ambiguity (TTFF) can be decided in less than two seconds, when the positioning accuracy of ambiguity-fixed solutions was assessed as the greater than or equal to one and two centimeters in horizontal and vertical, respectively. Comparing to the GPS-derived attitudes, the achievable accuracy gradually descended in sequence of yaw, pitch and roll due to the antenna geometric configuration. Furthermore, the RMSE values for the baseline lengths of three to six meters were within ±1′for yaw, and less than ±10′and ±20′for pitch and roll, respectively, but those of between six to fifteen meters were less than ±1′for yaw, ±5′for pitch, and ±10′for roll.

• Journal of Navigation and Port Research
• /
• v.46 no.6
• /
• pp.491-500
• /
• 2022

It has been noted that an accurate estimation of wind loads on offshore structures such as an FLNG (Liquefied Natural Gas Floating P roduction Storage Offloading Units, LNG FPSOs) with a large topside plays an important role in the safety design of hull and mooring system. Therefore, the present study aims to develop a computational model for estimating the wind load acting on an FLNG. In particular, it is the sequel to the previous research by the author. The numerical computation model in the present study was modified based on the previous research. Numerical analysis for estimating wind loads was performed in two conditions for an interval of wind direction (α), 15° over the range of 0° to 360°. One condition is uniform wind speed and the other is the NPD model reflecting the wind speed profile. At first, the effect of sand-grain roughness on the speed profile of the NPD model was studied. Based on the developed NPD model, mesh convergence tests were carried out for 3 wind headings, i.e. head, quartering, and beam. Finally, wind loads on 6-degrees of freedom were numerically estimated and compared by two boundary conditions, uniform speed, and the NPD model. In the present study, a commercial RANS-based viscous solver, STAR-CCM+ (ver. 17.02) was adopted. In summary, wind loads in surge and yaw from the wind speed profile boundary condition were increased by 20.35% and 34.27% at most. Particularly, the interval mean of sway (45° < α <135°, 225° < α < 315°) and roll (60° < α < 135°, 225° < α < 270°) increased by 15.60% and 10.89% against the uniform wind speed (10m/s) boundary condition.