• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2162-2167
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• 2014

Robots are widely used in various automation processes in industrial applications. Traditionally, it operated under fixed condition by teaching operating positions. Recently, diverse 2D/3D sensors are used together with robot to give more flexibility in operation. In this paper, we deal with automatic manipulation of tie rod in automotive production line. Sensor system consisted of a camera and slit laser is used for the acquisition of 3D information and it is used attached on the robot. Nut runner is used for the manipulation of stop nut and adjust bolt on the tie rod. Detailed procedures for the automatic manipulation of tie rod are presented. In the presented approach, we effectively use 3D information in whole procedure such as computing distance to the tie rod, rotation angle of bolt and nut. Experimental results show the feasibility of the proposed algorithm.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.558-561
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding Process in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noise such spatter and arc light. The adaptive Hough transformation was used to extract the laser stripe and to obtain specific weld points In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.516-519
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• 1996

Sub-assembly in ship manufacturing is a sequence of filet joint welding of stiffeners on metal panels and the process is different depending on companies. In this paper, we introduce a new intelligent robotic system of the sub-assembly process in Samsung Heavy Industry, where one shift of 22m * 9m workspace includes one to ten panels and each panel includes up to 10 stiffeners. The inherent problems such as several hundreds of different panels, unstructured task environment and the large scale do not allow a fixed automation, but needs highly intelligent versatile automation. The robotic system is composed of four 14DOF macro-mini robots and a task recognition system. Application of this system has verified the task specification such as low temperature environment(-10.deg. C) and productivity is satisfied successfully.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.320-323
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• 2002

This paper presents a new generation of system for pressure vessel and shipbuilding. Typical pressure vessel and ship building weld joint preparations are either traditional V, butt, fillet grooves or have narrow or semi narrow gap profiles. The fillet and U groove are prevalently used in heavy industries and shipbuilding to melt and join the parts. Since the wall thickness can be up to 6" or greater, welds must be made in many layers, each layer containing several passes. However, the welding time for the conventional processes such as SAW(Submerged Arc Welding) and FCAW(Flux Cored Arc Welding) can be many hours. Although SAW and FCAW are normally a mechanized process, pressure vessel and ship structures welding up to now have usually been controlled by a full time operator. The operator has typically been responsible for positioning each individual weld run, for setting weld process parameters, for maintaining flux and wire levels, for removing slag and so on. The aim of the system is to develop a high speed welding system with multitorch for increasing the production speed on the line and to remove the need for the operator so that the system can run automatically for the complete multi-torch multi-layer weld. To achieve this, a laser vision sensor, a rotating torch and an image processing algorithm have been made. Also, the multitorch welding system can be applicable for the fine grained steel because of the high welding speed and lower heat input compare to a conventional welding process.

• 한국지능시스템학회논문지
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• 제24권3호
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• pp.271-278
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• 2014

정지선과 횡단보도는 자율 주행에서 가장 기본적으로 인식해야 하는 인식대상임에도 불구하고 추출할 수 있는 특징이 매우 제한적이고 영상기반의 인식기술을 제외한 레이저나 RF, GPS/INS 인식기술로는 인식이 어려운 분야다. 이러한 이유로 이 분야에 대한 연구는 매우 제한적으로 수행되어왔다. 본 논문에서는 비전센서를 통해 입력된 정지선과 횡단보도 영상을 영상기반으로 인식할 수 있는 알고리즘을 설계하고 구현한다. 제안한 알고리즘은 3개 부분으로 구성된다. 즉 특징추출에 필요한 영역을 사전에 선정하여 처리속도를 향상시키는 관심영역 설정 부분, 일정비율 이상의 백색이 검출된 영상만 인식되도록 하여 불필요한 연산을 제거하는 색상패턴 검사 부분, 에지특징을 추출하고 추출된 에지특징을 사전에 모델링한 특징모델과 비교하여 정지선과 횡단보도 여부를 식별하는 특징 추출과 인식 부분이다. 특징추출과 인식 부분에는 유형별 특징비교 알고리즘을 적용하여 정지선과 횡단보도가 병행하여 존재하거나 각각 존재하는 경우에 대해 모두 식별되도록 한다. 또한 제안한 알고리즘은 기존연구를 발전시키기 위해 카메라의 차량내부 설치의 효과, 역광 및 그림자와 같은 다양한 제약조건에 대한 인식률 변화와 거리에 따른 적정 인식률 평가를 비교 분석하였다.