Target Recognition of Industrial Robots Using Machine Vision in 5G Environment

Jin, Zhenkun; Liu, Lei; Gong, Dafeng; Li, Lei

doi:10.3389/fnbot.2021.624466

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…With the development of artificial intelligence, robots have been widely used in various fields [ 33 , 34 , 35 ]. Among them, robot path planning is an important research problem.…”

Section: Robot Path-planning Problemmentioning

confidence: 99%

An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning

Yin

2023

Biomimetics

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This paper discusses a hybrid grey wolf optimizer utilizing a clone selection algorithm (pGWO-CSA) to overcome the disadvantages of a standard grey wolf optimizer (GWO), such as slow convergence speed, low accuracy in the single-peak function, and easily falling into local optimum in the multi-peak function and complex problems. The modifications of the proposed pGWO-CSA could be classified into the following three aspects. Firstly, a nonlinear function is used instead of a linear function for adjusting the iterative attenuation of the convergence factor to balance exploitation and exploration automatically. Then, an optimal α wolf is designed which will not be affected by the wolves β and δ with poor fitness in the position updating strategy; the second-best β wolf is designed, which will be affected by the low fitness value of the δ wolf. Finally, the cloning and super-mutation of the clonal selection algorithm (CSA) are introduced into GWO to enhance the ability to jump out of the local optimum. In the experimental part, 15 benchmark functions are selected to perform the function optimization tasks to reveal the performance of pGWO-CSA further. Due to the statistical analysis of the obtained experimental data, the pGWO-CSA is superior to these classical swarm intelligence algorithms, GWO, and related variants. Furthermore, in order to verify the applicability of the algorithm, it was applied to the robot path-planning problem and obtained excellent results.

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“…With the development of artificial intelligence, robots have been widely used in various fields [ 33 , 34 , 35 ]. Among them, robot path planning is an important research problem.…”

Section: Robot Path-planning Problemmentioning

confidence: 99%

An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning

Yin

2023

Biomimetics

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“…They provide thoughts for food packaging image positioning. [5] So this research presents a method of calculating image contour and object measurement to locate a single object. And this method is different from the mainstream HOG and SVM image localization methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Food Packaging Target Location and Recognition Technology Based on Machine Vision

Xiong

2023

AJST

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In the 21st century, people have an increased demand for food in their lives. Packaging manufacturers product a mass of outer packaging in order to satisfy the demand of food before they access to market for sale. What’s more, food packaging needs to be identified and tested, sorted, and shipped to the food producers. Machine vision has many advantages over than human eyes: high detection efficiency, high accuracy, no controlled by fatigue and so on. So, article takes the outer packaging of food as the research object and research on target location and recognition technology of food packaging based on machine vision was carried out. This article has certain practical application value. The research content is as follows. Firstly, the function of edge detection is recommended. Then three categories of edge detection are introduced. Through the five edge detections are introduced and the experimental results are compared, Canny algorithm is the best scheme. Secondly, this section learns the function and advantages of the HOG. The food packaging image is exacted features with HOG method. Thirdly, this section also introduces the function and the advantage of SIFT. The food packaging image features are taken experiments and recognized. Fourthly, this section recommends the experimental procedure and advantages of single target image location technique. In the end, this article concludes all the experiments and points out the shortcomings of the previous mentioned experimental steps.

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“…Due to the limitation of the detection space of the electric power equipment detection technology in the present stage, it is difficult to locate the fault in the process of detection, and it has a lot of problems facing the actual production process. At the same time, the defect will affect the performance of the power equipment, and when the processing of the image increases, the time of detection will increase, making it difficult to achieve the expected measurement of the expected measurement [10]- [12]. Therefore, using the quality detection of electric power equipment, the application of machine vision technology, and the experiment and analysis of the practical situation are of great significance [13].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Application of Machine Vision in the Automation Control of Power Electronic Equipment

Zhang

2024

Arch. Sci.

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This research centers on the application of machine vision in the automation control of power electronic equipment, and the purpose of the research is to improve the operation efficiency and safety of power equipment. The research combines PLC and IoT technology to build an intelligent monitoring system, which uses machine vision technology to recognize the state of power electronic equipment. The research results show that the system achieves 98\% accuracy in switchgear image recognition, and the SIFT algorithm performs superiorly in equipment state recognition, with the shortest recognition time being 7.17 seconds and the longest not exceeding 29.98 seconds. Machine vision technology effectively improves the automation and intelligence level of power equipment, which is of great significance to the development of power industry.

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Target Recognition of Industrial Robots Using Machine Vision in 5G Environment

Cited by 8 publications

References 28 publications

An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning

An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning

Food Packaging Target Location and Recognition Technology Based on Machine Vision

Analysis of the Application of Machine Vision in the Automation Control of Power Electronic Equipment

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