scholarly journals A Efficient System based on Model Segmentation for Weld Seam Grinding Robot

2021 ◽  
Author(s):  
Jimin Ge ◽  
Zhaohui Deng ◽  
Zhongyang Li ◽  
Wei Li ◽  
Tao Liu ◽  
...  
Keyword(s):  
Point Cloud ◽  
Weld Seam ◽  
Least Square Method ◽  
Space Structure ◽  
Least Square ◽  
Robotic Welding ◽  
Welding Seam ◽  
Efficient System ◽  
Extraction Algorithm ◽  
Grinding System

Abstract Uneven surface quality often occurs when butt welds are manually grinding, so robotic weld grinding automation has become a fast-developing trend. Weld seam extraction and trajectory planning are important for automatic control of grinding process. However, most of the research on weld extraction is focused on before welding. Due to the irregular shape of the weld after welding, and too little work has been devoted to the weld identification after welding. Consequently, in this paper, a novel simple and efficient weld extraction algorithm is proposed, and the robot grinding path is planned. Firstly, a new flexible bracket structure for welding seam extraction is designed. Secondly, the weld seam section profile model is established, and the processing of spatial point cloud problem is transformed into the processing of two-dimensional point cloud problem. The least square method (LSM) based on threshold comparison is used to segment the weld seam, which greatly improved the processing speed and accuracy. Then the grinding path and pose are obtained according to the extracted weld space structure. Finally, a robotic welding seam automatic grinding system is built. Experiments show that the proposed method could well extract the irregular weld contour after welding and the grinding system built is reliable, which greatly improves the grinding efficiency.

Novel Method for Extracting Body Boundary from Measured Point Cloud of Helical Surface

2011 ◽  
Vol 103 ◽  
pp. 63-67
Author(s):  
Yang Kuan Guo ◽  
Zhi Kang Pan ◽  
Hao Meng ◽  
Lian Qing Zhu ◽  
Pan Yi Wang
Keyword(s):  
Point Cloud ◽  
Least Square Method ◽  
Least Square ◽  
Rough Boundary ◽  
Helical Surface ◽  
Vector Method ◽  
Boundary Points ◽  
Body Boundary ◽  
Novel Method ◽  
Very High

A fast efficient method for extracting body boundary from helical surface is proposed in this paper in order to build the model of the measured surface. Firstly, according to the density of the point cloud, a divisional cylinder is built from an established model of the helical surface. Secondly, a center of the circle is get from the XY projection of the point cloud by the least-square method, and the points are sorted to make the point cloud in sequence. Then a vector method is used to test the remaining point cloud, which is separated by the divisional cylinder to obtain the rough body boundary points. The rough boundary is modified by the angles between the points to obtain the accurate body boundary points. Finally, a smooth boundary is formed through the B-spline method. The expereimental results show that the proposed method does not need grid partition and boundary grid detection and the efficiency is very high.

The Technology Research Based on Least Square Method for Extracting Quadric Surface

2012 ◽  
Vol 220-223 ◽  
pp. 2342-2345
Author(s):  
Y. W. Chen ◽  
H. X. Zhang ◽  
W. Y. Zhang
Keyword(s):  
Point Cloud ◽  
Least Square Method ◽  
Least Square ◽  
Single Type ◽  
Point Cloud Data ◽  
Quadric Surface ◽  
Cloud Data ◽  
Computation Efficiency ◽  
Noise Data ◽  
Linear Least Square

In this paper, the discrete point cloud data is directly used to extract quadric surface, with the single type of the point cloud data, the surface is firstly recognized. And then, according to different types of quadric surface, using the geometric parameter equation, the technology of extracting quadric surface can be achieved based on least square method. The results of the study show that: For normal data or less noisy data, the accuracy of calculation of linear least square method is the highest. For the nonlinear square method, on the other hand, the calculation precision is the lowest. However, the computational efficiency of the nonlinear least square method is higher than the linear least square method. The least square laws are more sensitive to noise data. With the increasing of the increased noise data, the extraction accuracy of the results will be affected by certain influence, but its computation efficiency is higher. Research results to practical engineering application of least square method to extract the quadratic surface have certain guiding significance.

scholarly journals ANALYSIS OF VISUAL NAVIGATION EXTRACTION ALGORITHM OF FARM ROBOT BASED ON DARK PRIMARY COLOUR

2020 ◽  
pp. 219-228
Author(s):  
Zhongkun Hou
Keyword(s):  
Precision Agriculture ◽  
Least Square Method ◽  
Visual Navigation ◽  
Least Square ◽  
Actual Situation ◽  
Extraction Technology ◽  
Navigation Path ◽  
New Development ◽  
Extraction Algorithm ◽  
Development Prospects

With the development of information technology, precision agriculture has also ushered in new development prospects. The use of farm robots to accurately identify the navigation path is of great significance for achieving accurate positioning of agriculture. In this study, when analysing the extraction algorithm of farm robot visual navigation based on dark primary colours, a method for pre-processing and edge detection of farmland images based on dark primary colours is proposed. At the same time, the least square method of linear fitting is used for the navigation path of agricultural robot, and then the fitting program is executed. On this basis, combined with the actual situation of outdoor farming and greenhouse cultivation of crops, the effectiveness of the robotic visual navigation extraction algorithm was verified. The research results show that for any form of farmland cultivation, image extraction technology based on dark primary colours can effectively distinguish between soil and crops, and the visual navigation path of farm robots fitted with least squares is basically linear, which is consistent with the commonly used crops for farm planting. The legal route is basically the same, and then the effectiveness of the extraction algorithm is verified. It is hoped that this study will provide a certain reference and reference for the analysis of the field navigation robot visual navigation extraction algorithm based on dark primary colours.

scholarly journals Analysis of Extraction Algorithm for Visual Navigation of Farm Robots Based on Dark Primary Colors

2021 ◽  
Vol 12 (2) ◽  
pp. 61-72
Author(s):  
Jin Wang ◽  
Yifei Cui ◽  
Hao Wang ◽  
Mohammad Ikbal ◽  
Mohammad Usama
Keyword(s):  
Image Processing ◽  
Least Square Method ◽  
Visual Navigation ◽  
Least Square ◽  
Gray Scale ◽  
Vertical Projection ◽  
Primary Color ◽  
Scale Method ◽  
Line Image ◽  
Extraction Algorithm

In order to quickly extract the visual navigation line of farmland robot, an extraction algorithm for dark primary agricultural machinery is proposed. The application of dark primary color principle in new farmland is made clearer by gray scale method, and the soil and crops are obviously separated, and the image processing technology of visual navigation line image of farmland is realized. In binary filtering of gray scale images, the maximum interclass variance method and morphological method are used respectively. The researchers use vertical projection method and least square method to the farmland interval extracted by navigation line. The farmland that needs the guide line image will be accurately located. It is found that the visual navigation extraction algorithm of farmland robot is widely used in the image extraction of navigation lines of various farmland roads and scenes compared with the traditional gray scale algorithm. Image processing has the advantages of clearer image processing.

A welding seam identification method based on cross-modal perception

2019 ◽  
Vol 46 (3) ◽  
pp. 453-459
Author(s):  
Xinde Li ◽  
Pei Li ◽  
Mohammad Omar Khyam ◽  
Xiangheng He ◽  
Shuzhi Sam Ge
Keyword(s):  
Real Time ◽  
Great Influence ◽  
Welding Process ◽  
Least Square Method ◽  
Least Square ◽  
Welding Fumes ◽  
Automatic Welding ◽  
Robust Method ◽  
Welding Seam ◽  
Content Type

Purpose As an automatic welding process may experience some disturbances caused by, for example, splashes and/or welding fumes, misalignments/poor positioning, thermally induced deformations, strong arc lights and diversified welding joints/grooves, precisely identifying the welding seam has a great influence on the welding quality. This paper aims to propose a robust method for identifying this seam based on cross-modal perception. Design/methodology/approach First, after a welding image obtained from a structured-light vision sensor (here laser and vision are integrated into a cross-modal perception sensor) is filtered, in a sufficiently small area, the extended Kalman filter is used to prevent possible disturbances to search for its laser stripe. Second, to realize the extraction of the profile of welding seam, the least square method is used to fit a sequence of centroids determined by the scanning result of columns displayed on the tracking window. Third, this profile is then qualitatively described and matched using a proposed character string method. Findings It is demonstrated that it maintains real time and is clearly superior in terms of accuracy and robustness, though its real-time performance is not the best. Originality/value This paper proposes a robust method for automatically identifying and tracking a welding seam.

Direct Assessment of Effective Renal Plasma Flow from Renoscintigraphy with a Gamma Camera and an On-Line Computer

1981 ◽  
Vol 20 (06) ◽  
pp. 274-278
Author(s):  
J. Liniecki ◽  
J. Bialobrzeski ◽  
Ewa Mlodkowska ◽  
M. J. Surma
Keyword(s):  
Count Rate ◽  
Renal Plasma Flow ◽  
Early Period ◽  
Least Square Method ◽  
Least Square ◽  
Uptake Coefficient ◽  
Positive Linear Correlation ◽  
On Line ◽  
Best Fit ◽  
Plasma Activity

A concept of a kidney uptake coefficient (UC) of 131I-o-hippurate was developed by analogy from the corresponding kidney clearance of blood plasma in the early period after injection of the hippurate. The UC for each kidney was defined as the count-rate over its ROI at a time shorter than the peak in the renoscintigraphic curve divided by the integral of the count-rate curve over the "blood"-ROI. A procedure for normalization of both curves against each other was also developed. The total kidney clearance of the hippurate was determined from the function of plasma activity concentration vs. time after a single injection; the determinations were made at 5, 10, 15, 20, 30, 45, 60, 75 and 90 min after intravenous administration of 131I-o-hippurate and the best-fit curve was obtained by means of the least-square method. When the UC was related to the absolute value of the clearance a positive linear correlation was found (r = 0.922, ρ > 0.99). Using this regression equation the clearance could be estimated in reverse from the uptake coefficient calculated solely on the basis of the renoscintigraphic curves without blood sampling. The errors of the estimate are compatible with the requirement of a fast appraisal of renal function for purposes of clinical diagknosis.

PENGARUH KNOWLEDGE MANAGEMENT, KOMPETENSI, MOTIVASI TERHADAP KINERJA KARYAWAN

2015 ◽  
Vol 5 (2) ◽  
pp. 1
Author(s):  
Miftahol Arifin
Keyword(s):  
Knowledge Management ◽  
Linear Regression ◽  
Significant Influence ◽  
Employee Performance ◽  
Least Square Method ◽  
Least Square ◽  
Analysis Tool ◽  
Ordinary Least Square ◽  
Competence Motivation ◽  
Performance Analyze

The purpose of this research is to analyze the influence of knowledge management on employee performance, analyze the effect of competence on employee performance, analyze the influence of motivation on employee performance). In this study, samples taken are structural employees PT.centris Kingdom Taxi Yogyakarta. The analysis tool in this study using multiple linear regression with Ordinary Least Square method (OLS). The conclusion of this study showed that the variables of knowledge management has a significant influence on employee performance, competence variables have an influence on employee performance, motivation variables have an influence on employee performance, The analysis showed that the variables of knowledge management, competence, motivation on employee performance.Keywords: knowledge management, competence, motivation, employee performance.

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