• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2468-2470
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• 2003

비주얼 서보잉이란 로봇팔 등과 같은 제어기의 폐루프에서 입력단에 영상을 이용하는 것이다. 영상에 나타난 정보는 특징점을 통해 얻을 수 있으며, 매시간 이 특징점의 위치를 추적함으로써 제어기의 출력값을 결정한다. Optical flow를 이용하는 가나데 특징점 추적기는 특징점 추적기 중에서 성능이 우수하다고 알려져 있다. 본 논문에서는 가나데 특징점 추적기를 이용하여 실시간으로 로봇팔을 제어하고 결과를 분석하도록 한다. 실험에 이용되는 로봇팔은 전체 6축이며 기존의 5축 상용로봇의 end-effector에 ccd카메라를 좌우로 회전가능하도록 기구부를 추가하였다. 6DOF를 갖도륵 변형된 로봇팔을 기구적으로 분석하고 자코비안을 획득한 후, 로봇팔의 end-effector에 설치된 카메라를 통하여 특정 영상이 얻어지도록 로봇의 end-effector의 속도를 생성해내고, 자코비안의 역행렬을 통해 로봇의 각 관절을 제어하는 과정을 기술하고 분석한다.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.358-365
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• 2017

In this paper, we propose an object recognition method using image information to improve the efficiency of visual servoingfor industrial manipulators in industry. This is an image-processing method for real-time responses to an abnormal situation or to external environment change in a work object by utilizing camera-image information of an industrial manipulator. The object recognition method proposed in this paper uses the Otsu method, a thresholding technique based on separation of the V channel containing color information and the S channel, in which it is easy to separate the background from the HSV channel in order to improve the recognition rate of the existing Harris Corner algorithm. Through this study, when the work object is not placed in the correct position due to external factors or from being twisted,the position is calculated and provided to the industrial manipulator.