• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2711-2722
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• 1993

Most of the current 2-D object recognition systems are model-based. In such systems, the representation of each of a known set of objects are precompiled and stored in a database of models. Later, they are used to recognize the image of an object in each instance. In this thesis, the approach method for the 2-D object recognition is treating an object boundary as a string of structral units and utilizing string matching to analyze the scenes. To reduce string matching time, models are rebuilt by means of fuzzy c-means clustering algorithm. In this experiments, the image of objects were taken at initial position of a robot from the CCD camera, and the models are consturcted by the proposed algorithm. After that the image of an unknown object is taken by the camera at a random position, and then the unknown object is identified by a comparison between the unknown object and models. Finally, the amount of translation and rotation of object from the initial position is computed.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.510-513
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• 2016

Detecting of the object in image processing is substantial but it depends on the object itself and the environment. An object can be detected either by its shape or color. Color is an essential for pattern recognition and computer vision. It is an attractive feature because of its simplicity and its robustness to scale changes and to detect the positions of the object. Generally, color of an object depends on its characteristics of the perceiving eye and brain. Physically, objects can be said to have color because of the light leaving their surfaces. Here, we conducted experiment in the aquarium fish tank. Different color of fish robots are mimic the natural swim of fish. Unfortunately, in the underwater medium, the colors are modified by attenuation and difficult to identify the color for moving objects. We consider the fish motion as a moving object and coordinates are found at every instinct of the aquarium to detect the position of the fish robot using OpenCV color detection. In this paper, we proposed to identify the position of the fish robot by their color and use the position data to control the fish robot gathering in one point in the fish tank through serial communication using RF module. It was verified by the performance test of detecting the position of the fish robot.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.60-70
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• 2000

In this paper a 3D position measuring device that finds the 3D position of an arbitarily placed object using a camersa system is introduced. The camera system consists of three stepping motors and a CCD camera and a laser. The viewing direction of the camera is controlled by two stepping motors (pan and tilt motors) and the direction of a laser is also controlled by a stepping motors(laser motor). If an object in a remote place is selected from a live video image the x,y,z coordinates of the object with respect to the reference coordinate system can be obtained by calculating the distance from the camera to the object using a structured light scheme and by obtaining the orientation of the camera that is controlled by two stepping motors. The angles o f stepping motors are controlled by a SGI O2 workstation through a parallel port. The mathematical model of the camera and the distance measuring system are calibrated to calculate an accurate position of the object. This 3D position measuring device can be used to acquire information that is necessary to monitor a remote place.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.933-938
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• 2001

In this paper, we describe a method for the mobile robot using images of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot`s position. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied to this method. Effectiveness of the proposed method is demonstrated by the simulation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.26-34
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• 1999

This study shows an alternative method for the determination of object's position, based on a computer vision method. This approach develops the vision system model to define the reciprocal relationship between the 3-D real space and 2-D image plane. The developed model involves the bilinear six-view parameters, which is estimated using the relationship between the camera space location and real coordinates of known position. Based on estimated parameters in independent cameras, the position of unknown object is accomplished using a sequential estimation scheme that permits data of unknown points in each of the 2-D image plane of cameras. This vision control methods the robust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the robot, and correct knowledge of the relative positions and orientation of the robot and CCD camera. Finally, the developed vision control method is tested experimentally by performing determination of object position in the space using computer vision system. These results show the presented method is precise and compatible.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1391-1401
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• 1995

This paper addresses design procedure and testing results of a closed-loop motion control of the cranes. When the object is stopped at the desired position, swinging occurs, and such swinging deteriorates the safety and efficiency of the operation of the crane. Therefore, in this paper, the cascade anti-swing and trolley position feedback controller are designed. Anti-swing controller rapidly eliminates swinging of object and position feedback controller reduces the trolley position error. The performance of this controller is investigated through the computer simulation and experiment. From the results of a series of computer simulations and experiments it can be concluded that proposed controller effectively reduces swinging of the object and trolley position error, which shows this controller can be used as an effective tool for the precise control of overhead cranes.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.276-276
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• 2000

This paper presents the efficient algorithms for the pose determination of a circular object with and without a priori knowledge of the object radius. The developed algorithms valid for a circular object are the result of the elaboration of Ma's work [2], which determines the pose of a conic object from two perspective views. First, the geometric constraint of a circular object and its projection on the image plane of a camera is described. The number of perspective views required for the object pose determination with and without a priori knowledge of the object radius is also discussed. Second, with a priori knowledge of the object radius, the pose of a circular object is determined from a single perspective view. The object pose information, expressed by two surface normal vectors and one position vector, is given in a closed form and with no ambiguity. Third, without a priori knowledge of the object radius, the pose of a circular object is determined from two perspective views. While the surface normal vectors are obtained from the first view, the position vector is obtained from the two views.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.513-518
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• 1993

In this paper, we consider the handling f a flexible object using dual-arm manipulators. We choose both the side arms as rigid, and the objects to be manipulated as flexible. Our purpose is to realize position control for the flexible object while suppressing its vibration. In particular, the problem taken up here is the stability of the control system while manipulating the object. We propose that the traditional approach to investigate the robot system be expanded to include the object's characteristics (thus transferring the stability of the robot system into the full assembly system). We define a handling characteristic while manipulating the object. Finally, the relationship between the handling characteristic and the positional constraint condition in the hold position of the arms is studied while considering the stability of the control system.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.204-216
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• 2006

Latest advances in hardware technology and state of the art of mobile robot and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. And mobile service robot requires the perception of its present position to coexist with humans and support humans effectively in populated environments. To realize these abilities, robot needs to keep track of relevant changes in the environment. This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace) is used in order to achieve these goals. This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used to estimate the location of moving robot. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot. Its performance is verified by computer simulation and experiment.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.235-242
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• 2008

An Autonomous mobile robot is a very useful system to achieve various tasks in dangerous environment, because it has the higher performance than a fixed base manipulator in terms of its operational workspace size as well as efficiency. A method for estimating the position of an object in the Cartesian coordinate system based upon the geometrical relationship between the image captured by 2-DOF active camera mounted on mobile robot and the real object, is proposed. With this position estimation, a method of determining an optimal path for the autonomous mobile robot from the current position to the position of object estimated by the image information using homogeneous matrices. Finally, the corresponding joint parameters to make the desired displacement are calculated to capture the object through the control of a mobile robot. The effectiveness of proposed method is demonstrated by the simulation and real experiments using the autonomous mobile robot.