• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2911-2914
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• 2003

Conventionally, biological manipulations have been performed manually with long training and pretty low success rates. To overcome this problem, a novel biological manipulation system has been developed to manipulate biological cells without any interference of a human operator, In this paper, we demonstrate a development of tole-autonomous Cell Manipulation System (CMS) using an image processing at a remote site. The CMS consists of two manipulators, a plane stage, and an optical microscope. We developed deformable template-model-matching algorithm for micro objects and pattern matching algorithm of end effect for these manipulators in order to control manipulators and the stage. Through manipulation of biological cells using these algorithms, the performance of the CMS is verified experimentally.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.343-349
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• 2012

To detect targets for autonomous navigation of unmanned ground vehicle, mounted sensors are required to work all-weather condition. In this point of view, the FMCW radar is quietly appropriate. In this paper, we present development results of target signal simulator for multi-beam type FMCW radar. A target signal simulator make pseudo target signals which simulates multiple moving targets. And we describe how to make hit information for each target in multi-beam type radar. The developed methods are utilized for target tracking device. Moreover it can be applied to similar target signal simulator.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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• pp.17-29
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• 2001

In this paper, we designed the hybrid path generation method which is named CAPM(Continuous path generation method based on artificial Potential field) that is able to be used in the obstacles environment. This CAPM was designed so that it puts together two obstacle avoidance algorithm-the continuous path generation method(CPGM) and the artificial potential field method(APFM). Here, the CAPM generate the safety path using continuous path curvature. But, this method has demerits when used in obstacles environment in which are closely located. Another method which is named the APFM generates the path with the artificial potential field in the obstacles environment. But, It has local minima in certain places and unnecessarily calculates the path in which obstacles are not located. So, the CAPM was designed for autonomous underwater vehicle(AUV) obstacle avoidance. As the result of simulation, it was confirmed that the CAPM can be applied to a safe path generation for AUV.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.26-27
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• 2012

Reflection considered as the view disturbing noise in optical systems, such as stereo camera in autonomous vehicles especially in night. Reflection caused by the street light or due to rainwater under adverse weather conditions. A blur image detected by the camera that results in wrong guidance to vehicle for detecting its track. A vehicle guidance approach through stereo vision can be same in day and night time. However it cannot be guided with same image analysis due to diverse illumination conditions. We develop the technique that shows its efficacy with illustrations of reflection removal off the camera lens and vehicle tracking control.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.161-167
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• 2006

In this paper, lateral force control of a mobile robot with slip is presented. First, the bicycle model of a mobile robot is derived for the front steering. Second, impedance force control algorithm is applied to regulate contact force with environment. The desired distance is specified conservatively inside the environment to guarantee to make contact. Different stiffness of environment has been tested for force tracking task. Simulation results show that the proposed control algorithm works well to maintain desired contact force on the environment.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.902-907
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• 2011

In this paper, we deal with performance evaluation of visual path following using 2D and 3D information. Visual path follow first teaches driving path by selecting milestone images then follows the same route by comparing the milestone image and current image. We follow the visual path following algorithm of [8] and [10]. In [8], a robot navigated with 2D image information only. But in [10], local 3D geometries are reconstructed between the milestone images in order to achieve fast feature prediction which allows the recovery from tracking failures. Experimental results including diverse indoor cases show performance of each algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.38-46
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• 2000

In this paper, robust depth and course controllers of AUV(autonomous underwater vehicles) using LMI-based H$_{\infty}$ servo control are proposed. The $H_{\infty}$ servo problem is modified to an $H_{\infty}$ control problem for the generalized plant that includes a reference input mode, and then a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach. The robust depth and course controllers are designed to be satisfied the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under sea wave and tide disturbances. The performances of the designed controllers are evaluated by computer simulations, and these simulation results show the applicability of the proposed robust depth and course controller.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.173.4-173
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• 2001

This paper presents a stable nonlinear adaptive control for AUV(Autonomous Underwater Vehicle) by using neural network. AUV's dynamics are highly nonlinear, and their hydrodynamic coefficients vary with different operational conditions. In this paper, the nonlinear uncertainties of the AUV's dynamics are approximated by using LPNN(Linearly parameterized Neural Network). The presented controller is consist of three parallel terms; linear feedback control, sliding mode control, and adaptive control(LPNN). Lyapunov theory is used to guarantee the stability of tracking errors and neural network´s weights errors. Numerical simulations for nonlinear control of the AUV show the effectiveness of the proposed techniques.

• Journal of Mechanical Science and Technology
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• v.20 no.8
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• pp.1159-1168
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• 2006

In this paper, a new revolute mobile robot arm with five degree of freedom (d.o.f) was developed for autonomous moving robots. As a control system for the robot arm, a distributed control system composed of the main controller and five motor controllers for arm joints was developed. The main controller and the motor controllers w ε re developed using the ARM microprocessor and the TMS320c2407 microprocessor, respectively. A new trajectory tracking algorithm for the motor controllers was devised employing pre-generated off-line trajectory data. Also, a 3-D simulator based on the openGL software to simulate the motion of the robot arm was developed. To validate the performance of the robot system, experiments to track a specified trajectory were performed.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.182-188
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• 2011

This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.