• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.108-115
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• 2011

This paper describes a new sensor system for mobile robot motion estimation using stereo infrared light sources and a camera. Visibility is being applied to robotic obstacle avoidance path planning and localization. Using simple visibility computation, the environment is partitioned into many visibility sectors. Based on the recognized edges, the sector a robot belongs to is identified and this greatly reduces the search area for localization. Geometric modeling of the vision system enables the estimation of the characteristic pixel position with respect to the robot movement. Finite difference analysis is used for incremental movement and the error sources are investigated. With two characteristic points in the image such as vertices, the robot position and orientation are successfully estimated.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.70-74
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• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• Current Optics and Photonics
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• v.1 no.6
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• pp.573-578
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• 2017

Position estimation of a sound source based on time difference of arrival at an array of three acousto-optic sensors is introduced. Each sensor consists of a Mach-Zehnder interferometer including a sensing part in one arm that is a piece of fiber surrounded by membrane in order to enhance the acousto-optic effect. Estimation error of a recorded gunshot sound signal was evaluated with the theoretically calculated values for two different locations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.400-406
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• 2006

Knowledge of camera parameters, such as position, orientation and focal length, is essential to 3D information recovery or virtual object insertion. This paper analyzes the error sensitivity of focal length due to position error of feature points which are employed for self-calibration. We verify the dependency of the focal length on the distance from the principal point to feature points with simulations, and propose a criterion for feature selection to reduce the error sensitivity.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.84-90
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• 2019

Tremendous computation of full search or lossless motion estimation algorithms for video coding has led development of many fast motion estimation algorithms. We still need proper control of computation and prediction quality. In the paper, we suggest an algorithm that reduces computation effectively and controls computational amount and prediction quality, while keeping prediction quality as almost the same as that of the full search. The proposed algorithm uses multiple thresholds for partial block sum and times of counting unchanged minimum position for each step. It also calculates the partial block matching error, removes impossible candidates early, implements fast motion estimation by comparing times of keeping the position of minimum error for each step, and controls prediction quality and computation easily by adjusting the thresholds. The proposed algorithm can be combined with conventional fast motion estimation algorithms as well as by itself, further reduce computation while keeping the prediction quality as almost same as the algorithms, and prove it in the experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2292-2297
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• 2010

To improve the performances of Sawyer motors and to regulate yaw rotation, various feedback control methods have been developed. Almost all of these methods require information on the position, velocity or full state of the motor. Therefore, in this paper, a nonlinear observer is designed to estimate the full state of the four forcers in a Sawyer motor. The proposed method estimates the full state using only positional feedback. Generally, Sawyer motors are operated within a yaw magnitude of several degrees; outside of this range, Sawyer motors step out. Therefore, this observer design assumes that the yaw is within ${\pm}90^\b{o}$. The convergence of the estimation error is proven using the Lyapunov method. The proposed observer guarantees that the estimation error globally exponentially converges to zero for all arbitrary initial conditions. Furthermore, since the proposed observer does not require any transformation, it may result in a reduction in the commutation delay. The simulation results show the performance of the proposed observer.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.319.1-319
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• 2002

A frequency-domain PES estimation and its prediction method are proposed for the tightly-coupled servo/mechanical design of high-TPI HDD system above 100kTPI. The major two disturbance energies which are related with mechanical vibrations inside of HDD are used to predict the drive-level PES, while considering closed-loop servo dynamics. One is the torque disturbance which mainly comes from aerodynamic excitation of HSA system and the other is the displacement disturbance from disk-spindle dynamics. (omitted)

• Journal of the Korean Society for Precision Engineering
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• v.25 no.10
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• pp.58-66
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• 2008

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.347-353
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• 2019

Electric-hydraulic sever cylinders are used in many offshore applications such as wind energy farms, solar farms and plants. Jack-up barges are often used for these offshore system operations. Jack-up barge control is up/down by hydraulic cylinder position control. Working in harsh environments can lead to changes in internal parameters. This nonlinearity makes precise control difficult. In order to overcome the problems, we proposed a method of unknown-parameter estimation algorithm based on measurements obtained by system. In this paper, we employee Unscented Kalman filter (UKF) to estimate states and unknown-parameter from augmented nonlinear equation. Performance of estimation results is verified in simulation on an environments of Matlab. The estimation results of the state and unknown-parameter show that the estimation error of unknown-parameter is reduced according to decreasing the state estimation error.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.10a
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• pp.75-78
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• 2004

A mesh generation algorithm adapted to the mesh density map using the Delaunay mesh generation technique is developed. In the finite element analyses of the forging processes, the numerical error increases as the process goes on because of discrete property of the finite elements or severe distortion of elements. Especially, in the region where stresses and strains are concentrated, the numerical discretization error will be highly increased. However, it is too time consuming to use a uniformly fine mesh in the whole domain to reduce the expected numerical error. Therefore, it is necessary to construct locally refined mesh at the region where the error is concentrated such as at the die corner. In this study, the point insertion algorithm is used and the mesh size is controlled by moving nodes to optimized positions according to a mesh density map constructed with a posteriori error estimation. An optimization technique is adopted to obtain a good position of nodes. And optimized smoothing techniques are also adopted to have smooth distribution of the mesh and improve the mesh element quality.