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 RESEARCH ON VISUAL NAVIGATION PATH DETECTION METHOD FOR DENSE PLUM GROVE

2021 ◽  
pp. 111-118
Author(s):  
XiaoDan Ren ◽  
Haichao Wang ◽  
Xin Shi
Keyword(s):  
Color Space ◽  
Region Of Interest ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Visual Navigation ◽  
Least Square ◽  
Detection Accuracy ◽  
Navigation Path ◽  
Field Management ◽  
Path Detection

Aiming at the field management of plum grove in Inner Mongolia of China, taking the dense planting plum groves in Bikeqi town of Hohhot City as the research object, this paper proposed a visual navigation path detection algorithm for plum grove. By processing the video image information of plum grove, comparing RGB and HSV color space model, HSV color model was selected to separate the plant and background in V channel. Homomorphic filtering was used to highlight the region of interest in the image, Otsu was selected to segment the image, the intersection of plum trunk and ground was extracted as feature points, and the least square method was used to fit the navigation path. Through the comparative analysis of detection rate under different detection conditions in one day, the verification test of route accuracy was carried out. The experimental results show that: for dense planting plum grove, the average path detection accuracy of the algorithm is 70% and 73.3% under the condition of front light and weak light, respectively. The detection accuracy and real-time meet the requirements of plum grove field management, and the navigation baseline can be generated more accurately, which provides a preliminary basis for the realization of mechanical vision navigation in plum grove field management.

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.

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.

A New Method of Extraction of Mobile Robot Navigation Line Based on Edge Detection

2010 ◽  
Vol 143-144 ◽  
pp. 482-486
Author(s):  
Ji Wen Dong ◽  
Hui Ming Lv
Keyword(s):  
Edge Detection ◽  
Mobile Robot ◽  
Least Square Method ◽  
Visual Navigation ◽  
Least Square ◽  
New Method ◽  
Mobile Robot Navigation ◽  
Line Extraction ◽  
Three Stages ◽  
Method Of Extraction

The extraction of ground navigation line is one of the basic technologies of mobile robot visual navigation. Due to the shortcomings of traditional Hough transform and the least square method to extract navigation line, a new method of navigation line extraction based on edge detection is proposed in this paper, which includes three stages: image preprocessing, morphology de-noising and edge detection. First, using monocular camera to collect image of navigation line laid on the ground in advance and preprocesses the collected image, and then using morphology to remove separated points and empties, finally, detects the edge of the processed image, and calculates the slope of navigation line according to the calculated midpoints, then computed the deviated angle of the robot according to the slope and adjusted in real time in order to achieve navigation. Results of experiments show that the method has good feasibility.

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.

An Application of the Least Square Method to the Ship Maneuverability Identification

1973 ◽  
Vol 1973 (134) ◽  
pp. 173-181
Author(s):  
Takeo Koyama ◽  
Takane Watanabe ◽  
Iwao Watanabe
Keyword(s):  
Least Square Method ◽  
Least Square ◽  
Ship Maneuverability

Peristaltic Carreau-Yasuda nanofluid flow and mixed heat transfer analysis in an asymmetric vertical and tapered wavy wall channel

2020 ◽  
Vol 1 (1) ◽  
pp. 128-140 ◽  
Author(s):  
Mohammad Hatami ◽  
◽  
D Jing ◽  
Keyword(s):  
Heat Transfer ◽  
Least Square Method ◽  
Weissenberg Number ◽  
Least Square ◽  
Heat Transfer Analysis ◽  
Phase Method ◽  
Nanofluid Flow ◽  
Two Phase ◽  
Nanoparticles Concentration ◽  
The Right

In this study, two-phase asymmetric peristaltic Carreau-Yasuda nanofluid flow in a vertical and tapered wavy channel is demonstrated and the mixed heat transfer analysis is considered for it. For the modeling, two-phase method is considered to be able to study the nanoparticles concentration as a separate phase. Also it is assumed that peristaltic waves travel along X-axis at a constant speed, c. Furthermore, constant temperatures and constant nanoparticle concentrations are considered for both, left and right walls. This study aims at an analytical solution of the problem by means of least square method (LSM) using the Maple 15.0 mathematical software. Numerical outcomes will be compared. Finally, the effects of most important parameters (Weissenberg number, Prandtl number, Brownian motion parameter, thermophoresis parameter, local temperature and nanoparticle Grashof numbers) on the velocities, temperature and nanoparticles concentration functions are presented. As an important outcome, on the left side of the channel, increasing the Grashof numbers leads to a reduction in velocity profiles, while on the right side, it is the other way around.

Fast noise removal algorithm for HDR image based on least square method

2009 ◽  
Vol 29 (4) ◽  
pp. 994-996
Author(s):  
De-quan SUN ◽  
Jun ZHANG ◽  
Xiao-feng LI ◽  
Hui LI
Keyword(s):  
Least Square Method ◽  
Noise Removal ◽  
Least Square ◽  
Hdr Image
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