The Research on the Robot Vision System Based on the Target Clamping Technology

2012 ◽  
Vol 430-432 ◽  
pp. 1929-1934
Author(s):  
Huai Xing Wen ◽  
Wen Sheng Wang
Keyword(s):  
Visual Recognition ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Target Object ◽  
Recognition Algorithms

Introduces the structure and the components of industrial robot vision system. Through designing the gripping point, the location of the clamping point can be planned out in the clamping operation, and then by visual recognition algorithms to calculate the coordinate figure of the clamping point relative to the camera. Then the calculated values would transmitted to computer, by whose control of the robot’s move can the operation of clamping on the target object be achieved.

Research on the Visual Recognition Algorithm for Loading Robot Vision System

2012 ◽  
Vol 271-272 ◽  
pp. 1645-1648
Author(s):  
Yong Tao Yang ◽  
Huai Xing Wen
Keyword(s):  
Approximation Algorithm ◽  
Stereo Vision ◽  
Visual Recognition ◽  
Object Segmentation ◽  
Vision System ◽  
Robot Vision ◽  
Target Object ◽  
Recognition Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

In order to study the questions about the recognition of relative position for the operating object and calculation of the object volume in the loading robot binocular stereo vision system. Based on the characteristics of the operating object, proposed the method that use of its vertices only to match the corresponding point of the camera imaging for location identification, also raised the approximation algorithm that firstly, cut up the whole, followed by calculate the volume of the various parts, then carry out the sum of the each segmentation volume. Experiments and analysis showed that the distance of camera and the object greater affect the visual system, less impact on the intensity of light；In the target object segmentation， the number of partition k=11 is better. Both methods produced the small errors for the visual recognition of the system, it can meet actual needs.

Embedded Robot Vision System Based on DSP

2015 ◽  
Vol 734 ◽  
pp. 168-171
Author(s):  
Xing Ze Li ◽  
Ling Zhu ◽  
Yi Hua
Keyword(s):  
System Design ◽  
Real Time ◽  
Robot Control ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Ccd Camera ◽  
Target Object ◽  
The Real ◽  
Time Problem

Aim at the real-time problem of industrial robot vision system, design a embedded robot vision system based on DSP microprocessor. This system can use CCD camera and the ultrasonic sensor to collect the target environment information. It also can use the processor DSP to process the images and recognize target. And then through the communication module, send results in the form of wireless to the upper computer, providing target object information for robot control layer. This system completes the software and hardware system design, image collection & processing and robot control, as well as meet the real-time requirements of machine vision system.

scholarly journals Industrial Robot Vision System

1983 ◽  
Vol 16 (20) ◽  
pp. 337-341
Author(s):  
V.M. Grishkin ◽  
F.M. Kulakov
Keyword(s):  
Vision System ◽  
Industrial Robot ◽  
Robot Vision

Study on Industrial Automation with SCARA Robot Vision System Design

2013 ◽  
Vol 675 ◽  
pp. 72-76 ◽  
Author(s):  
Xin Wu ◽  
Hong Yin He ◽  
Gong Jin Lan ◽  
Jin Tian Tang
Keyword(s):  
Vision System ◽  
Center Of Mass ◽  
Robot Vision ◽  
Target Object ◽  
Object Identification ◽  
Initial Image ◽  
Industrial Automation ◽  
Scara Robot ◽  
Filtering Method ◽  
Good Object

To realize scara robot in industrial automation work environment identifying target objects independently, this paper puts forward a kind of machine vision solution based on opencv . First the k neighbor average filtering method and otsu is used to the initial image filtering and segmentation, and given a method based on pixel area, using the target object itself geometric characteristics and center of mass calibration to identify, locate purpose. The experimental results show that the system can achieve good object identification orientation effect in more complex industrial automation environment, so as to provide the necessary information for scara robot to grab target objects.This kind of robot vision system play an important role in industrial automation.

Target Location of Industrial Robot Based on Vision

2014 ◽  
Vol 945-949 ◽  
pp. 1478-1481
Author(s):  
Gui Hong Jia
Keyword(s):  
Target Location ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Contour Extraction ◽  
Multiple Target ◽  
Segmentation Method ◽  
Target Image ◽  
Black And White ◽  
Centroid Position

Vision is the most important way to obtain information from the word. This paper collected the target image using industrial robot vision system, and We get Black and white images using binary image segmentation method, then the contour of each object in the image can be obtained with edge detection and contour extraction, The centroid position was confirmed using minimum enclosing rectangle method after gaining the outline of target. The experimental results show that this method can quickly and accurately obtain multiple target centroid position.

scholarly journals A Vision Calibration Method of Robot based on Halcon

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Calibration Method ◽  
System Calibration ◽  
Radial Distortion ◽  
Vision Control ◽  
Calibration Accuracy ◽  
The Relationship ◽  
Research Hotspots

Visual calibration is an important researchdirection in the field of robot vision control, and is also one of thecurrent research hotspots. In this paper, the principle of softwarecalibration is described in detail, and a software calibrationmethod based on Halcon optimization is studied and designed. Byusing the operator in the function library, the internal andexternal parameters of the camera are calibrated. The influence ofthe terminal center of the robot and the radial distortion of thecamera lens is fully considered. The method is used to establish thecamera. The relationship between the image coordinated systemand the robot world coordinated system. Experiments show thatthe method has high calibration accuracy and practicability, andis suitable for industrial robot vision system calibration.

scholarly journals Intelligent Perception System of Robot Visual Servo for Complex Industrial Environment

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7121
Author(s):  
Yongchao Luo ◽  
Shipeng Li ◽  
Di Li
Keyword(s):  
Visual Information ◽  
Vision System ◽  
Industrial Robot ◽  
Robot Vision ◽  
Region Of Interest ◽  
Servo System ◽  
Experimental Result ◽  
Visual Servo ◽  
Industrial Environment ◽  
Perception System

Robot control based on visual information perception is a hot topic in the industrial robot domain and makes robots capable of doing more things in a complex environment. However, complex visual background in an industrial environment brings great difficulties in recognizing the target image, especially when a target is small or far from the sensor. Therefore, target recognition is the first problem that should be addressed in a visual servo system. This paper considers common complex constraints in industrial environments and proposes a You Only Look Once Version 2 Region of Interest (YOLO-v2-ROI) neural network image processing algorithm based on machine learning. The proposed algorithm combines the advantages of YOLO (You Only Look Once) rapid detection with effective identification of ROI (Region of Interest) pooling structure, which can quickly locate and identify different objects in different fields of view. This method can also lead the robot vision system to recognize and classify a target object automatically, improve robot vision system efficiency, avoid blind movement, and reduce the calculation load. The proposed algorithm is verified by experiments. The experimental result shows that the learning algorithm constructed in this paper has real-time image-detection speed and demonstrates strong adaptability and recognition ability when processing images with complex backgrounds, such as different backgrounds, lighting, or perspectives. In addition, this algorithm can also effectively identify and locate visual targets, which improves the environmental adaptability of a visual servo system

scholarly journals A Novel Robot Vision Applicable to Real-time Target Tracking

2003 ◽  
Vol 15 (2) ◽  
pp. 185-191 ◽  
Author(s):  
Kazuhiro Shimonomura ◽  
◽  
Keisuke Inoue ◽  
Seiji Kameda ◽  
Tetsuya Yagi ◽  
...  
Keyword(s):  
Target Tracking ◽  
Real Time ◽  
Vision System ◽  
Robot Vision ◽  
Target Object ◽  
Frame Rate ◽  
Video Frame ◽  
Intelligent Sensor ◽  
Analog Cmos ◽  
Silicon Retina

We designed a vision system with a novel architecture composed of a silicon retina, an analog CMOS VLSI intelligent sensor, and FPGA. Two basic pre-processes are done with the silicon retina: a Laplacian-Gaussian (∇2G)-like spatial filtering and a subtraction of consecutive frames. Analog outputs of the silicon retina were binarized and transferred to FPGA in which digital image processing was executed. The system was applied to real-time target tracking under indoor illumination. Namely, the center of a target object was found as the median of the binarized image. The object could be tracked within the video frame rate in indoor illumination. The system has a compact hardware and a low power consumption and therefore is suitable for robot vision.

A Robot Vision System Based on Two-Dimensional Object-Oriented Models

1986 ◽  
Vol 16 (4) ◽  
pp. 582-589 ◽  
Author(s):  
Lorenz A. Schmitt ◽  
William A. Gruver ◽  
Assad Ansari
Keyword(s):  
Vision System ◽  
Robot Vision ◽  
Object Oriented ◽  
Two Dimensional ◽  
Dimensional Object
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