• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.4
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• pp.723-729
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• 2001

We are able to work on the shared virtual space in Web-based Collaborative Design System using only Internet and Web browser. The users connect to the Solid Modeler Server through m and they create 3D shape and manipulate them variously. Then the users will share 3D objects and two problems can arise. The users must be able to pick the objects effectively which they want to manipulate. When one of the users manipulates a particular object, others should not disturb with the same object. In this paper, picking is implemented not only by computing intersection of mouse pointer with the objects of the virtual world, but also by using capabilities and attributes of scene graph node, by setting bounds intersection testing instead of geometric intersection testing, by limiting the scope of the pick testing, using Java 3D. These methods can reduce the computation of picking and can pick 3D objects effectively and easily using the system of hierarchy. To have effective concurrency, we used shared lock and exclusive lock as the action in work space.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.58-67
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• 2006

Due to the variety of signal processing and complicated mathematical analysis, it is not easy to accomplish 3D bin-picking with non-contact sensor. To solve this difficulties the reliable signal processing algorithm and a good sensing device has been recommended. In this research, 3D laser scanner and CCD camera is applied as a sensing device respectively. With these sensor we develop a two-step bin-picking method and reliable algorithm for the recognition of 3D bin object. In the proposed bin-picking, the problem is reduced to 2D intial recognition with CCD camera at first, and then 3D pose detection with a laser scanner. To get a good movement in the robot base frame, the hand eye calibration between robot's end effector and sensing device should be also carried out. In this paper, we examine auto-calibration technique in the sensor calibration step. A new thinning algorithm and constrained hough transform is also studied for the robustness in the real environment usage. From the experimental results, we could see the robust bin-picking operation under the non-aligned 3D hole object.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.631-633
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• 2001

협동설계시스템에서의 공유 오브젝트는 3D 도형이 되며, 사용자가 임의의 오브젝트를 picking하는 문제와 그 오브젝트에 어떤 조작을 취할 때 동시성제어(concurrency)하는 문제가 생긴다. 본 논문에서는 오브젝트의 picking이 마우스 포인터에서의 ray와 오브젝트간에 intersection을 계산하는 방법 외에 scene graph의 노드에 picking 속성을 주는 방법, bounds를 설정하는 방법, picking test의 범위를 한정하는 방법을 사용하여 computation의 부담을 줄이고 효과적인 동시성제어가 이루어지도록 action에 따라 공유(shared)lock과 전용(exclusive)lock을 사용한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.255-256
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• 2019

본 논문에서는 물체를 집기(picking) 위해 필요한 깊이 값을 특수카메라인 리얼센스를 사용하여 받아와서 2D 카메라로는 하지 못하는 로봇 팔 피킹 시스템을 구현하였다. 객체 인식은 텐서플로우 객체 검출 라이브러리를 사용하여 정확도를 높였고, ROS 기반의 rviz, moveit, gazebo 등의 패키지를 사용하여 아두이노와 통신하며 로봇팔 하드웨어로 인식된 객체를 피킹하는 시스템을 구현하였다.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.231-233
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• 2007

In this paper we present a new visual approach for the robust bin-picking in a two-step concept for a vision driven automatic handling robot. The technology described here is based on two types of sensors: 3D laser scanner and CCD video camera. The geometry and pose(position and orientation) information of bin contents was reconstructed from the camera and laser sensor. these information can be employed to guide the robotic arm. A new thinning algorithm and constrained hough transform method is also explained in this paper. Consequently, the developed bin-picking demonstrate the successful operation with 3D hole object.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.248-254
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• 1993

This paper proposes the labeling method for solving bin-picking problem in robot vision. It has the processing steps such as image thresholding, region labeling, and moment computation. To determine a target object from object, the modified labeling method is used to. The moment concept applied to determine the position and orientation of target object. Finally, some experiment result are illustrated and compared with the results of conventional shrinking algorithm and collision fronts algorithm. The proposed labeling method has reduced processing time.

• Annual Conference of KIPS
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• 2001.04a
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• pp.349-352
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• 2001

웹 기반 협동설계시스템은 인터넷망과 웹브라우저를 이용하여 공유된 가상 공간에서 협동작업이 이루어지도록 한다. 이때 공유 오브젝트는 3D 도형이 되며, 사용자가 임의의 오브젝트를 선택하여 조작하기 위하여 picking이 효과적으로 이루어져야 한다. 본 논문에서는 오브젝트의 picking이 마우스 포인터에서의 ray와 오브젝트간에 intersection을 계산하는 방법 외에 Java 3D API를 이용하여 scene graph의 노드에 picking 속성을 주는 방법, bounds를 설정하는 방법, picking test의 범위를 한정하는 방법을 사용하여 computation의 부담을 줄이고 효과적인 picking이 이루어지도록 한다.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.839-846
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• 2016

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.

• Journal of Biosystems Engineering
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• v.28 no.5
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• pp.449-456
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• 2003

A robot system was developed to pick desired colony. This robot system consisted of an image acquisition process which acquires the image information of colony, an illumination device which irradiates the object once when it gets the image of it, a picking head, a replicating head, a bed for fixing well-plates, and a sterilization device of sterilizing pin stained with colony. Picking pins were washed in an ultrasonic wave washing for takes ten seconds. Picking pins were dipped for sterilizing in alcohol for ten seconds. The time for resterilizing picking pins in a heater was five seconds. This performance test resulted 100% success rate for both the colony picking and the colony replication process. Considering the procedure in which 8 pins were smeared by colony, picked on a well plate, and sterilized as one cycle, the system could carry out one cycle in 110 seconds. It took about 138 minutes to pick around 600 colonies.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1014-1017
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• 1992

This paper proposed LM method for solving bin-picking problem in robot vision. It has the processing steps such as image enchancement, image thresholding, region labelling, and moment computation. To determine a target object form bined objects, the modified labelling method is used. To determine position and orientation of holdsite, the moment method is used. Finally, some experiment results are illustated and compared with the results of conventional shrinking algorithm. The proposed LM method has reduced processing time.