• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1458-1463
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• 2004

Tracking is one of the most important pre-required task for many application such as human-computer interaction through gesture and face recognition, motion analysis, visual servoing, augment reality, industrial assembly and robot obstacle avoidance. Recently, 3D information of object is required in realtime for many aforementioned applications. 3D tracking is difficult problem to solve because during the image formation process of the camera, explicit 3D information about objects in the scene is lost. Recently, many vision system use stereo camera especially for 3D tracking. The 3D feature based tracking(3DFBT) which is on of the 3D tracking system using stereo vision have many advantage compare to other tracking methods. If we assumed the correspondence problem which is one of the subproblem of 3DFBT is solved, the accuracy of tracking depends on the accuracy of camera calibration. However, The existing calibration method based on accurate camera model so that modelling error and weakness to lens distortion are embedded. Therefore, this thesis proposes 3D feature based tracking method using SVM which is used to solve reconstruction problem.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.540-543
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• 1997

In this paper, a precise trajectory tracking method for mobile robot using a vision system is presented. In solving the problem of precise trajectory tracking, a hierarchical control structure is used which is composed of the path planer, vision system, and dynamic controller. When designing the dynamic controller, non-ideal conditions such as parameter variation, frictional force, and external disturbance are considered. The proposed controller can learn bounded control input for repetitive or periodic dynamics compensation which provides robust and adaptive learning capability. Moreover, the usage of vision system makes mobile robot compensate the cumulative location error which exists when relative sensor like encoder is used to locate the position of mobile robot. The effectiveness of the proposed control scheme is shown through computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.584-587
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• 2002

A vision sensor measure range data using laser light source. This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which needs laster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2357-2359
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• 1998

This paper proposes trajectory tracking of the moving object based on one camera vision system. And, this system proposes a method which robot manipulator grips moving object and predicts coordinate of moving objcet. The trajectory tracking and position coordinate are computed by vision data acquired to camera. Robot manipulator tracks and grips moving object by vision data. The proposed vision systems use a algorithm to do real-time processing.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1816-1819
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• 1997

Using the vision system, robotic tasks in unstructured environments can be accompished, which reduces greatly the cost and steup time for the robotic system to fit to he well-defined and structured working environments. This paper proposes a dynamic control scheme for robot manipulator with eye-in-hand camera configuration. To perfom the tasks defined in the image plane, the camera motion Jacobian (image Jacobian) matrix is used to transform the camera motion to the objection position change. In addition, the dynamic learning controller is designed to improve the tracking performance of robotic system. the proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.

• Journal of Welding and Joining
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• v.16 no.6
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• pp.68-76
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• 1998

A CCD camera with a laser stripe was applied to realized the automatic weld seam tracking. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path. The adaptive Hough transformation was used to extract laser stripes an to obtain specific weld points. It takes relatively long time to process image on-line control using the basic control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The dead zone, where the sensing of weld line is impossible, was eliminated by rotating the camera with its rotating axis centered at the weld torch. When weld lines were detected, the camera angle was controlled in order to get the minimum image data for sensing of weld lines. Consequently, the image processing time was reduced.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.92-99
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding systems, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, novel presented, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1105-1109
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• 1995

A CCD-camera, which is structured with vision system, was used to realize automatic seam-tracking system and 3-D information which is needed to generate torch path, was obtained by using laser-slip beam. To extract laser strip and obtain welding-specific point, Adaptive Hough-transformation was used. Although the basic Hough transformation takes too much time to process image on line, it has a tendency to be robust to the noises as like spatter. For that reson, it was complemented with Adaptive Hough transformation to have an on-line processing ability for scanning a welding-specific point. the dead zone,where the sensing of weld line is impossible, is eliminated by rotating the camera with its rotating axis centered at welding torch. The camera angle is controlled so as to get the minimum image data for the sensing of weld line, hence the image processing time is reduced. The fuzzy controller is adapted to control the camera angle.

• 한국정보디스플레이학회:학술대회논문집
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• 2000.01a
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• pp.79-80
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• 2000

General stereo vision system shows things in 3D, using two visions of left and right side. When the viewpoints of left/right sides are not in accord with each other, it gives fatigue to human eyes and prevents them from having the 3-D feeling. Also, it would be difficult to track mobile objects that are not in the middle of a screen. Therefore, the object tracking function of stereo vision system is to control tracking objects to always be in the middle of a screen while controlling convergence angles of mobile objects in the input image of the left/right cameras. In this paper, object-tracker in stereo vision system is presented which would track mobile objects by using block matching algorithm of preprocessing and JTC.