• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.128.6-128
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• 2001

In this paper, we present a methodology of sensing and control for a robot system designed to be capable of grasping an object and moving it to target point Stereo vision system is employed to determine to depth map which represents the distance from the camera. In stereo vision system we have used a center-referenced projection to represent the discrete match space for stereo correspondence. This center-referenced disparity space contains new occlusion points in addition to the match points which we exploit to create a concise representation of correspondence an occlusion. And from the depth map we find the target object´s pose and position in 3-D space. To find the target object´s pose and position, we use the method of the model-based recognition.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.2
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• pp.62-68
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• 1998

This paper presents the application of computer vision for the purpose of determining the position of the unknown object in the plane. The presented control method is to estimate the six view parameters representing the relationship between the image plane coordinates and the real physical coordinates. The estimation of six parameters is indispensable for transforming the 2-dimensional camera coordinates to the 3-dimensional spatial coordinates. Then, the position of unknown point is estimated based on the estimated parameters depending on the cameras. The suitability of this control scheme is demonstrated experimentally by determining position of the unknown object in the plane.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.231-240
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• 2015

In this paper, it was presented to design and analyze the kinematics of grasping a rigid object by means of multi-degrees-of-freedom hand fingers. It is shown firstly that a set of kinematic equation describing dynamics system of the arm and object together with geometric constraint of tight area-contacts is formulated by Lagrange's equation. It has been presented secondly that the problems of controlling both the forces of pressing object and the rotation angle of the object under the geometric constraints are discussed. In this research, the control method for static stable grasping and enhancing dexterity in manipulating things is proposed. It is illustrated by computer simulation that the control system gives the performance improvement in the kinematic grasping of the hand fingers of robot.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.536-546
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• 2003

We propose an object extraction technique adequate for the radial shape's radar signal structure for the purpose of implementing ARPA(Automatic Radar Plotting Aid) installed in the vessel. The radar signal data are processed by interpolation and accumulation to acquire a qualified image. The objects of the radar image have characteristics of having different shape and size as it gets far from the center, and it is not adequate for clustering generally. Therefore, this study designs a new vigilance distance model of elliptical shape and adopts this model in the ART2 neural network. We prove that the proposed clustering method makes it possible to extract objects adaptively and to separate the connected objects effectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.155-163
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• 2000

In this paper, we propose an algorithm for the object function used in optimal control or optimal design that sets the object function as simultaneous and then calculates the optimal value according to the Newton method. The proposed method calculates the optimal value simply using two inputs; object function and initial value, using the DDA(Direct Derivative Algorithm) which is a programmed ordinary derivative function that does not inquire the calculation of derivative function nor any inputs. And we have verified the usefulness of the algorithm for the optimal control and optimal dosing.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.349-352
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• 1994

An object recognition and restoration using ultrasound sensors and neural networks are presented. The planar arrangement of the sensor is used to reduce the interference effects between sensors. The SOFM(Self-Organizing Feature Map) Neural Network and SCL(Simple Competitive Learning) method are learned with the acquired data. Lab experiments were performed that the object can be recognized ed the resolutions of the object can be enhanced by using the small number of the ultrasound array and neural networks.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.5-77
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• 2001

A Robot vision system with a visual skill so as take information for arbitrary target or object has been applied to auto-inspection and assembling system. It catches the moving target with the manipulator by using the information from the vision system. The robot needs some information where the moving object will place after certain time. A camera is fixed on a robot manipulator, not on the fixed support outside of the robot. It secures wider working area than the fixed camera, and it dedicates to auto scanning of the object. It computes some information on the object center, angle and speed by vision data, and can guess grabbing spot by arriving time. When the location ...

• Journal of the Korean Society of Industry Convergence
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• v.20 no.4
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• pp.299-305
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• 2017

This study proposes a new technique to design and control of robot hand gripper for assembling and disassembling of a machine parts. The motion equation describing dynamics of the manipulators and object together with geometric constraint is formulated by Lagrange-Euler's equation. And the problems of controlling both the grasping force and the rotation angle of the grasped object under the constraints are analyzed. The effect of geometric constraints and a method of computer simulation for overall system is verified. Finally, it is illustrated that even in case of there exists a sensory feedback from sensing data of the rotational angle of the object to command inputs control of joint and this feedback connection from sensing data to control grasping of machinery parts.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.459-466
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• 2000

In this paper, we propose an attitude controller for an unstructured object using CMG(Control Moment of Gyro) subsystem, which has a stabilizer function. The CMG subsystem consists of one motor for spinning the wheel and the other motor for turning the outer gimbal. While the wheel of CMG subsystem is spinning at high speed, applying force to the spin axis of the wheel leads the torque about the vertical axis. We utilize the torque to control the attitude of object in this study. For the stabilizer function, in additiion, holding the load at the current position, the power applied to the gimbal motor of CMG will be cut, which result in the braking force to stop the load by gyro effect. However, due to the gear reduction connected to outer gimbal, slow load motion cannot generate the braking force. Thus, in this study, we are willing to make a holding force by applying control power to the gimbal motor from the signal of piezoelectric gyroscopic sensor that detected the angular velocity of the load. These two features are demonstrated in experiment, carrying a beam with crane. As a result, load was started to rotate by controlling gimbal positiion and was stopped by turning off the gimbal power. Moreover, slow movement of the load was also rejected by additional control with gyroscopic sensor.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.263-266
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• 1994

Recently, complicated and dexterous tasks with two or more arms are needed in ninny robot manipulator applications which can not be accomplished with one manipulator. In general, when two arms manipulate an object, tile dynamics of the arms and the object should be considered simultaneously. In order to control the force of tile arms, we can use various control schemes based upon dynamic modeling. But, there are difficulties in solving inverse dynamics equations, and the environment where a manipulator performs various tasks is usually unknown, and we can not describe a model precisely, for instances, the effect of the joint flexibility, and the friction between the arm and the object. Therefore, in this paper, we suggest a new force control method employing fuzzy inference without solving dynamic equations. Fuzzy inference rules and parameters are designed and adjusted with the automatic fuzzy modeling method using the Hough transform and gradient descent method.