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 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

scholarly journals Experiments on mobile robot stereo vision system calibration under hardware imperfection

2018 ◽  
Vol 161 ◽  
pp. 03020 ◽  
Author(s):  
Ramil Safin ◽  
Roman Lavrenov ◽  
Subir Kumar Saha ◽  
Evgeni Magid
Keyword(s):  
Mobile Robot ◽  
Stereo Vision ◽  
Experimental Approach ◽  
Vision System ◽  
Robot Vision ◽  
System Calibration ◽  
Stereo Vision System ◽  
Calibration Methods ◽  
Vertical Level ◽  
Grid Based

Calibration is essential for any robot vision system for achieving high accuracy in deriving objects metric information. One of typical requirements for a stereo vison system in order to obtain better calibration results is to guarantee that both cameras keep the same vertical level. However, cameras may be displaced due to severe conditions of a robot operating or some other circumstances. This paper presents our experimental approach to the problem of a mobile robot stereo vision system calibration under a hardware imperfection. In our experiments, we used crawler-type mobile robot «Servosila Engineer». Stereo system cameras of the robot were displaced relative to each other, causing loss of surrounding environment information. We implemented and verified checkerboard and circle grid based calibration methods. The two methods comparison demonstrated that a circle grid based calibration should be preferred over a classical checkerboard calibration approach.

scholarly journals Computer Vision Tool-Setting System of Numerical Control Machine Tool

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5302
Author(s):  
Bo Hou ◽  
Congpeng Zhang ◽  
Shoubo Yang
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Performance Testing ◽  
Calibration Method ◽  
Numerical Control ◽  
Cnc Machine ◽  
Control Machine Tool ◽  
System Calibration ◽  
Tool Setting ◽  
Automatic Tool

An automatic tool-setting and workpiece online detecting system was proposed to study the key technologies of next-generation intelligent vision computerized numerical control (CNC) machines. A computer vision automatic tool-setting system for a CNC machine was set up on the basis of the vision tool-setting principle. A rapid vision calibration method based on the position feedback from the CNC machine was proposed on the basis of the theory of traditional vision system calibration. The coordinate mapping relationship of the image and the CNC machine, the tool-setting mark point on the workpiece, and the tool tip were calibrated. The vision system performance testing and system calibration experiments were performed. Experimental results indicated that the time consumption was 128 ms in image processing. The precision of tool setting and measuring was less than 1 μm. The workpiece positioning and processing online detection function of the system can completely meet the requirements of visual CNC machine application, and the system has wide application prospects.

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.

Research on the Calibration Technology of Robot Vision System

2012 ◽  
Vol 482-484 ◽  
pp. 506-511
Author(s):  
Jian Qiang Wang ◽  
Li Song Chen ◽  
Jiu You Zhu ◽  
Zhao Long Niu ◽  
Dong Hua Tang
Keyword(s):  
Coordinate Transformation ◽  
Vision System ◽  
Image Acquisition ◽  
Robot Vision ◽  
Calibration Technique ◽  
Car Body ◽  
The Relationship

This paper introduces calibration technique for robot vision system, aiming to enhance the robot’s ability to adapt to various environments. In accordance with a calibration plate and car body, we figured out the relationship among the coordinates of car body, camera, and robot by image acquisition, processing, analysis, and calculation. An algorithm was developed to deduce the coordinate transformation between robot frame and calibration plate frame with 4 points. Its feasibility was validated by the experiment.

scholarly journals A Decoupled Calibration Method for Camera Intrinsic Parameters and Distortion Coefficients

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Kun Yan ◽  
Hong Tian ◽  
Enhai Liu ◽  
Rujin Zhao ◽  
Yuzhen Hong ◽  
...  
Keyword(s):  
Real Data ◽  
Calibration Method ◽  
Intrinsic Parameters ◽  
Radial Distortion ◽  
Vision Measurement ◽  
Field Of Vision ◽  
Marquardt Algorithm ◽  
Calibration Accuracy ◽  
Camera Intrinsic Parameters ◽  
Division Model

Camera calibration is a necessary process in the field of vision measurement. In this paper, we propose a flexible and high-accuracy method to calibrate a camera. Firstly, we compute the center of radial distortion, which is important to obtain optimal results. Then, based on the radial distortion of the division model, the camera intrinsic parameters and distortion coefficients are solved in a linear way independently. Finally, the intrinsic parameters of the camera are optimized via the Levenberg-Marquardt algorithm. In the proposed method, the distortion coefficients and intrinsic parameters are successfully decoupled; calibration accuracy is further improved through the subsequent optimization process. Moreover, whether it is for relatively small image distortion or distortion larger image, utilizing our method can get a good result. Both simulation and real data experiment demonstrate the robustness and accuracy of the proposed method. Experimental results show that the proposed method can be obtaining a higher accuracy than the classical methods.

scholarly journals Research on Vision System Calibration Method of Forestry Mobile Robots

2021 ◽  
Vol 14 ◽  
pp. 1107-1114
Author(s):  
Ruting Yao ◽  
Yili Zheng ◽  
Fengjun Chen ◽  
Jian Wu ◽  
Hui Wang
Keyword(s):  
Mobile Robots ◽  
Autonomous Navigation ◽  
Time Synchronization ◽  
Vision System ◽  
Robot Vision ◽  
Nonlinear Least Squares ◽  
Calibration Method ◽  
Time Operation ◽  
Spatial Calibration ◽  
Low Efficiency

Forestry mobile robots can effectively solve the problems of low efficiency and poor safety in the forestry operation process. To realize the autonomous navigation of forestry mobile robots, a vision system consisting of a monocular camera and two-dimensional LiDAR and its calibration method are investigated. First, the adaptive algorithm is used to synchronize the data captured by the two in time. Second, a calibration board with a convex checkerboard is designed for the spatial calibration of the devices. The nonlinear least squares algorithm is employed to solve and optimize the external parameters. The experimental results show that the time synchronization precision of this calibration method is 0.0082s, the communication rate is 23Hz, and the gradient tolerance of spatial calibration is 8.55e−07. The calibration results satisfy the requirements of real-time operation and accuracy of the forestry mobile robot vision system. Furthermore, the engineering applications of the vision system are discussed herein. This study lays the foundation for further forestry mobile robots research, which is relevant to intelligent forest machines.

The Application Research of Robot Vision Target Positioning Based on Static Camera Calibration

2013 ◽  
Vol 712-715 ◽  
pp. 2378-2384
Author(s):  
Jiang Yan Yin
Keyword(s):  
Camera Calibration ◽  
Vision System ◽  
Research Work ◽  
Robot Vision ◽  
Target Position ◽  
Calibration Method ◽  
Lens Distortion ◽  
Application Research ◽  
Distortion Coefficient ◽  
Key Techniques

Target precise positioning by vision system is one of key techniques in robot vision system. In target positioning and selection with robot vision technique, the camera lens distortion must be calibrated. In this paper, a calibration method based on segment slope is used to calibrate the camera and the radial lens distortion coefficient is obtained. The distortion coefficient is used in calculating target position coordinates, and the robot end-exceutor is led to position the target with the use of the coordinates. The experimental results show the effectiveness of the research work. Keywords:robot vision;camera calibration;radial distortion;target positioning

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