Implementation of Two Cameras to Robotic Cell for Recognition of Components

Sukop, Marek

doi:10.4028/www.scientific.net/amm.282.167

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…The development of 3D robot vision is actually based on the improvement of vision algorithms and 3D sensors. 2 Through decades of innovation, vision algorithms in the robot vision system have formed three classes: human–robot interaction, 3 –13 identification and perception, 14 –20 and movement decision. 21 –34 Corresponding to these classes, the main applications contain gesture recognition, 3,5,9,11,12,35 target tracking, 10,36 –39 human eye tracking, 13,40 map building, 20,25,41 –44 scene understanding, 33,34 object recognition, 16 –19,45,46 location and pose recognition, 21 –23 autonomous navigation,…”

Section: Introductionmentioning

confidence: 99%

“…The development of 3D robot vision is actually based on the improvement of vision algorithms and 3D sensors. 2 Through decades of innovation, vision algorithms in the robot vision system have formed three classes: humanrobot interaction, [3][4][5][6][7][8][9][10][11][12][13] identification and perception, [14][15][16][17][18][19][20] and movement decision. [21][22][23][24][25][26][27][28][29][30][31][32][33][34] Corresponding to these classes, the main applications contain gesture recognition, 3,5,9,11,12,35 target tracking, 10,[36][37][38][39] human eye tracking, 13,40 map building, 20,25,…”

Section: Introductionmentioning

confidence: 99%

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Advances in sensing and processing methods for three-dimensional robot vision

Chen

2018

International Journal of Advanced Robotic Systems

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In this article, we survey the recent developments of sensing methods in three-dimensional robot vision, centering on the current three-dimensional sensors and core techniques embedded in robotic systems. Over 8000 publications have reported rather wide application areas of three-dimensional robot vision in the last 40 years, such as human-robot interaction, object recognition, three-dimensional modeling, object tracking, searching and surveillance, as well as robot manipulation, localization, navigation, mapping, and path planning. Representative works and future research trends are also addressed in this article.

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Section: Introductionmentioning

confidence: 99%

“…The development of 3D robot vision is actually based on the improvement of vision algorithms and 3D sensors. 2 Through decades of innovation, vision algorithms in the robot vision system have formed three classes: humanrobot interaction, [3][4][5][6][7][8][9][10][11][12][13] identification and perception, [14][15][16][17][18][19][20] and movement decision. [21][22][23][24][25][26][27][28][29][30][31][32][33][34] Corresponding to these classes, the main applications contain gesture recognition, 3,5,9,11,12,35 target tracking, 10,[36][37][38][39] human eye tracking, 13,40 map building, 20,25,…”

Section: Introductionmentioning

confidence: 99%

Advances in sensing and processing methods for three-dimensional robot vision

Chen

2018

International Journal of Advanced Robotic Systems

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Smart Camera for Simple Sorting Tasks

Juruš

Koukolová

2018

TST

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Urgency of the research. Attendance time places great emphasis on the production cavity. No manufacturing enterprise can afford to neglect the automation and modernization of its processes. That's why a company focused on manufacturing automotive accessories has turned to us. Target setting. Output checkboxes prepared at the end of the production process were made by people. This control was unreliable and its reliability was diminishing with the increasing working time. An increasing number of claimed cases required the company to choose a new solution to the problem. We were asked to design a workplace using a camera to read the box descriptions so that it could be followed by palletizing. The second goal was to consider the possibility of subsequent ro-botization. Uninvestigated parts of general matters defining. We do not deal with the basic principles of image processing. Basic image processing performs camera software and uses the higher search features of objects. The research objective. In this article, we are working on implementing the visual system into real-life operation. Design a simple solution that meets customer requirements, whose economic return would be interesting. The statement of basic materials. We use a simple camera with area capture. It captures frames as an area map of pixels. Basic black and white transition detection is selected for basic object recognition. A description made on white paper that is used as a box description makes it easy to recognize objects in the background. Conclusions. The proposed test facility consists of a frame, a camera and a conveyor. The workplace produces only 25 cubes per minute under test conditions. To increase productivity, it is advisable to extend the number of posts. The camera was also selected for its ability to communicate with the robot interface. The program creates code that is compatible with the robot's control program and defines the position of the goods in the space. This makes it easy to connect and then robotize the workstation if the company decides for this solution.

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Identification of Randomly Distributed Objects

Jánoš

Varga

2015

AMM

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This article describes the possibilities of identifying a randomly distributed objects due to the removal of parts from the conveyor belt, which is part of the workplace for assembly of the components. A specific feature of this work is that the installation is carried out with the robot SCARA, which take parts from the conveyor. Parts on the conveyor are unoriented, therefore it is necessary to use a camera system to detect the position and orientation of parts. Because of this, it is necessary to carry out the control lines across the moving conveyor. Recognition, identification, location and orientation of the proposed method is sufficiently robust and easily adaptable to the different type of components.

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Implementation of Two Cameras to Robotic Cell for Recognition of Components

Cited by 3 publications

References 6 publications

Advances in sensing and processing methods for three-dimensional robot vision

Advances in sensing and processing methods for three-dimensional robot vision

Smart Camera for Simple Sorting Tasks

Identification of Randomly Distributed Objects

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