• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1158-1162
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• 2005

Drug delivery systems have been developed to reduce the side toxicity of drugs by localizing them in the site of action. But it depends on the circulation of the blood and it doesn't have the function of locomotive mechanism of itself for searching for the region of disease. However, this problem could be solved by nanobot which have the locomotive function. So, we mimic the movement of cell that can move in a human body. In this paper, to polymerize the encapsulated actin within the liposome, electroporation technique is employed. In order to optimize polymerization and depolymerization of the liposome, we compare the time of polymerization and depolymerization by concentration of crown ether. we synthesis the liposome which contain azobenzene Linked crown Ether conjugated Actin protein. Azobenze linked crown ether holds the K+ ion by exposure of UV light and this disturbs the actin polymerization. In result, UV light could control the liposome growth. Finally, we could develop the liposome robot and control the growth and degeneration of the liposome by external stimuli such s UV light. The merit of the controlling by UV light doesn't need to inject proteins which induce polymerization and depolymerization of actin protein.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.320-325
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• 2016

This paper presents a robust finite-time sliding mode control (SMC) scheme for unknown disturbance and unmodeled nonlinear friction and dynamics in the robotic manipulator. A finite-time SMC (FSMC) surface and finite-time sliding mode controller are constructed to obtain faster error convergence than the conventional infinite-time based SMC. By adding prescribed constraint control term to a finite-time SMC to compensate for unknown disturbance and uncertainties, a robust control scheme can be designed as well as faster convergence control. In addition, simpler controller structure is built by using feed-forwarding upper bound coefficients of each manipulator dynamic parameters instead of model-based control or adaptive observer to estimate unknown manipulator parameters. Simulation and experimental evaluations highlight the efficacy of the proposed control scheme for an articulated robotic manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.807-813
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• 2011

High precision of planning in the preoperative phase can contribute to increase operational safety during computer-aided spinal fusion surgery, which requires extreme caution on the part of the surgeon, due to the complexity and delicacy of the procedure. In this paper, an advanced preoperative planning framework for spinal fusion is presented. The framework is based on spinal pedicle data obtained from CT (Computed Tomography) images, and provides optimal insertion trajectories and pedicle screw sizes. The proposed approach begins with safety margin estimation for each potential insertion trajectory that passes through the pedicle volume, followed by procedures to collect a set of insertion trajectories that satisfy operation safety objectives. The radius of a pedicle screw was chosen as 70% of the pedicle radius. This framework has been tested on 68 spinal pedicles of 8 patients requiring spinal fusion. It was successfully applied, resulting in an average success rate of 100% and a final safety margin of $2.44{\pm}0.51mm$.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1226-1232
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• 2010

A door can serve as a feature for place classification and localization for navigation of a mobile robot in indoor environments. This paper proposes a door detection method based on the recognition of various door handles using the general Hough transform (GHT) and support vector machine (SVM). The contour and color histogram of a door handle extracted from the database are used in GHT and SVM, respectively. The door recognition scheme consists of four steps. The first step determines the region of interest (ROI) images defined by the color information and the environment around the door handle for stable recognition. In the second step, the door handle is recognized using the GHT method from the ROI image and the image patches are extracted from the position of the recognized door handle. In the third step, the extracted patch is classified whether it is the image patch of a door handle or not using the SVM classifier. The door position is probabilistically determined by the recognized door handle. Experimental results show that the proposed method can recognize various door handles and detect doors in a robust manner.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1147-1152
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• 2014

This paper describes the design of a four-axis force/torque sensor with PSPBs (Parallel Step Plate Beams). The sensor is composed of eight PSPBs, a force/torque transmitting block, and fixing blocks. It is designed by using the FEM(Finite Element Method), and fabricated by using strain gages. The characteristic tests of the sensor are carried out, and the interference error, repeatability error, and non-linearity error are less than 2.21%, 0.03% and 0.03%. Furthermore, the structure of the four-axis force/torque sensor with PSPBs has a larger rated capacity than that of the four-axis force/torque sensor with PPBs under the same overall sensor size and the same rated output. It is thought that the developed four-axis force/torque sensor with PSPBs can be used for measuring the forces and torques in an intelligent robot, automation devices, etc.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.835-841
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• 2014

In this paper we propose a swing-up strategy for a single inverted pendulum. The proposed method has a feature whereby can handle the input and output constraint of a pendulum in a systematic way. For the swing-up of a pendulum, we adopt a 2-DOF control structure that combines the feedforward and feedback control. In order to generate the swing-up feedforward trajectories that satisfy the input and output constraint, we formulate the problem of generating feedforward trajectories as a nonlinear optimal control problem subject to constraints. We illustrate that the proposed method is more flexible than the existing method and provides great freedom in choosing the actuator of the inverted pendulum. Through an experiment, we show that the proposed method can swing a pendulum upward effectively while satisfying all the imposed constraints.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.341-348
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• 2013

A location estimation algorithm based on the sea-surface beacon is proposed in this paper. The beacon is utilized to provide ultrasonic signals to the underwater vehicles around the beacon to estimate precise position of underwater vehicles (ROV, AUV, Diver robot), which is named as USBL (Ultra Short Baseline) system. It utilizes GPS and INS data for estimating its position and adopts DWT (Discrete Wavelet Transform) de-noising filter and UKF (Unscented KALMAN Filter) elaborating the position estimation. The beacon system aims at estimating the precise position of underwater vehicle by using USBL to receive the tracking signals. The most important one for the precise position estimation of underwater vehicle is estimating the position of the beacon system precisely. Since the beacon is on the sea-waves, the received GPS signals are noisy and unstable most of times. Therefore, the INS data (gyroscope sensor, accelerometer, magnetic compass) are obtained at the beacon on the sea-surface to compensate for the inaccuracy of the GPS data. The noises in the acceleration data from INS data are reduced by using DWT de-noising filter in this research. Finally the UKF localization system is proposed in this paper and the system performance is verified by real experiments.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.1
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• pp.25-30
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• 2014

In this paper, we have implemented an FMCW radar for a near distance measurement. In the structure of the FMCW radar, it is a key problem to solve the VCO nonlinearity. In this work, we have adopted a VCO nonlinearity compensation algorithm using the spectrum correlation of beat signals. The radar experimented in this work uses an X-band(9.55~10.25GHz) microwave signal, and realizes precision of 3% in the range of 30m. The prototype can be applied to the front surveillance radar such as in vehicle anti-collision and probing robot mission.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.111-114
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• 1997

Usually, Evolutionary Algorithms are considered more efficient for optimal system design, However, the performance of the system is determined by fitness function and system environment. In this paper, in order to overcome the limitation of the performance by this factor, we propose a co-evolutionary method that two populations constantly interact and coevolve. In this paper, we apply coevolution to neural network's evolving. So, one population is composed of the structure of neural networks and other population is composed of training patterns. The structure of neural networks evolve to optimal structure and, at the same time, training patterns coevolve to feature patterns. This method prevent the system from the limitation of the performance by random design of neural network structure and inadequate selection of training patterns. In this time neural networks are trained by evolution strategies that are able to apply to the unsupervised learning. And in the coding of neural networks, we propose the method to maintain nonredundancy and character preservingness that are essential factor of genetic coding. We show the validity and the effectiveness of the proposed scheme by applying it to the visual servoing of RV-M2 robot manipulators.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.164-170
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• 2004

This paper proposes a Distributed Autonomous Robotic System(AIS) based on Artificial Immune System(AIS) and Distributed Genetic Algorithm(DGA). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: dispersion and aggregation. AIS decides one among above two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the DGA in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.