• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.121-128
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• 2011

As high precision industries such as semiconductor, TFT-LCD manufacturing and MEMS continue to grow, the demand for higher DOF precision stages has been increasing. In general, the stages should accommodate a prescribed range of payloads in order to position various precision manufacturing/inspection instruments. Therefore a nonlinear controller using sliding motion is developed, which bears mass perturbation and makes the upper plate of the stage move in 6 DOF. For the application of the nonlinear control, an observer is also developed based on expected noise covariance. To eliminate the steady state error of step response, integral terms are inserted into the state-space model. The linear term of the controller is designed using optimization scheme in which parameters can be weighted according to their physical significance, whereas the nonlinear term of the controller is designed using trial and error method. A comprehensive simulation study proves that the designed controller is robust against mass perturbation and completely eliminates steady state errors.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.5
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• pp.354-361
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• 2016

Parallel robots are usually used for performing pick-and-place motion to increase productivity in high-speed environments. The present study proposes a high-speed parallel robot and a control approach to improve the tracking performance for the purpose of handling a solar cell. However, the target processes are not limited to the solar cell-handling field. Therefore, a delta-type parallel manipulator is designed, and a ball joint structure is specifically proposed to increase the allowed angle that would meet the required workspace. A control algorithm considering the synchronization between multiple joints in a closed-chain mechanism is also suggested to improve the tracking performance, where the tracking and synchronization errors are simultaneously considered. In addition, a prototype machine with the proposed ball joint is implemented. A satisfactory tracking performance is achieved by applying the proposed control algorithm, with a cycle time of 0.3 s for a 0.1 kg payload.

• Journal of Sensor Science and Technology
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• v.24 no.3
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• pp.175-180
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• 2015

Worldwide, studies on intelligent vehicles for the convenience of drivers have been actively conducted as the number of cars has increased. However, vehicle convenience enabled by buttons lowers the concentration on driving and hence poses as a huge threat to the safety of the driver. The use of one of the convenient features, impaired driving auxiliary equipment, is limited because of its complex usage, and this device also hinders the front view of the driver. This paper proposes a vehicle-control device for controlling the convenient features as well as changes in speed and direction using gestures and motions of the driver. This device consists of an ultrasonic sensor for recognizing movement, an arduino for accepting signal control functions and servo and DC motors apply to various vehicle parts. Firstly, the vehicle-control device was designed using a 3D CAD program known as Solid-works based on the size of the steering wheel. Then, through simulations, a suitable length for minimizing the absorbent between ultrasonic sensors was confirmed using a program known as COMSOL Multiphysics. Finally, simulation results were verified through experiments, and the optimal size of the device was identified through the number of errors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4971-4987
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• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1233-1252
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• 2015

This study investigates the problem of crack detection in post-buckled beam-type structures. The beam under the axial compressive force has a crack, assumed to be open and through the width. The crack, which is modeled by a massless rotational spring, divides the beam into two segments. The crack detection is considered as an optimization problem, and the weighted sum of the squared errors between the measured and computed natural frequencies is minimized by the bees algorithm. To find the natural frequencies, the governing nonlinear equations of motion for the post-buckled state are first derived. The solution of the nonlinear differential equations of the two segments consists of static and dynamic parts. The differential quadrature method along with an arc length strategy is used to solve the static part, while the same method is utilized for the solution of the linearized dynamic part and the extraction of the natural frequencies of the cracked beam. The investigation includes several numerical as well as experimental case studies on the post-buckled simply supported and clamped-clamped beams having open cracks. The results show that several parameters such as the amount of applied compressive force and boundary conditions influences the outcome of the crack detection scheme. The identification results also show that the crack position and depth can be predicted well by the presented method.

• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.283-289
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• 2010

Recent advance of digital camera results in that image signal processing techniques are widely adopted to railroad security management. However, due to the nature of railroad management many images are acquired in low light level environment such as night scenes. The lack of light causes lots of noise in the image, which degrades image quality and causes errors in the next processes. 3D noise reducing techniques produce better results by using consecutive sequence of images. On the other hand, they cause degradation such as motion blur if there are motions in the sequence. In this paper, we use an adaptive weight filter to estimate more accurate motions and use the result of the adaptive filter to 3D result to improve objective and subjective mage quality.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.403-410
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• 2016

This paper proposes a robust image-based visual servoing scheme using a nonlinear observer for a monocular eye-in-hand manipulator. The proposed control method is divided into a range estimation phase and a target-tracking phase. In the range estimation phase, the range from the camera to the target is estimated under the non-moving target condition to solve the uncertainty of an interaction matrix. Then, in the target-tracking phase, the feature point uncertainty caused by the unknown motion of the target is estimated and feature point errors converge sufficiently near to zero through compensation for the feature point uncertainty.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.552-555
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• 2018

This study developed a gesture recognition method using Kinect sensor and proposed a fighting action control interface. To extract the pattern features of a gesture, it used a method of extracting them in consideration of a body rate based on the shoulders, rather than of absolute positions. Although the same gesture is made, the positional coordinates of each joint caught by Kinect sensor can be different depending on a length and direction of the arm. Therefore, this study applied principal component analysis in order for gesture modeling and analysis. The method helps to reduce the effects of data errors and bring about dimensional contraction effect. In addition, this study proposed a modified matching algorithm to reduce motion restrictions of gesture recognition system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.1063-1075
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• 2000

This paper proposes an adaptive error concealment technique for compressed video. Since redundancy is extracted out during compression process, compressed video is vulnerable to errors which occur during transmission of video over error prone networks such as wireless channels and Internet. Error concealment is a process of reconstructing video out of damaged video bit stream. We proved that scalable encoding is very useful for error concealment. Analysis of experiments shows that some part of image is better concealed by using base layer information and other part of image is better concealed by using previous frame information. We developed a technique which enables to decide which methodology is more effective, adaptively, based on motion vectors and regional spatial activity. We used H.263v2 for scalable encoding, but, our approach could be applied to all DCT based video codec.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.533-542
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• 2008

Background subtraction from video data is one of the most important task in various realtime machine vision applications. In this paper, a new scheme for background subtraction based on the hexagonal pixel sampling is proposed. Generally it has been found that hexagonal spatial sampling yields smaller quantization errors and remarkably improves the understanding of connectivity. We try to apply the hexagonally sampled image to the LBP based non-parametric background subtraction algorithm. Our scheme makes it possible to omit the bilinear pixel interpolation step during the local binary pattern generation process, and, consequently, can reduce the computation time. Experimental results revealed that our approach based on hexagonal spatial sampling is very efficient and can be utilized in various background subtraction applications.