scholarly journals Research on Application of Machine Vision in Robots for Live-Power Lines

2021 ◽  
Vol 257 ◽  
pp. 01046
Author(s):  
Han Wu ◽  
Jianye Huang ◽  
Shuang Lin ◽  
Bingqian Liu ◽  
Yuanliang Fan ◽  
...  

The electric fire-exchanging operation is basically used to implement operation such as Wire stripping, drainage wire through the fastening wire clip, clamp bolt fastening, etc. Manual operation is time-consuming and laborious and has very high safety risks, so the automatic electrified ignition robot emerges as The Times require; The automatic operation method should accurately identify the position of wire and drainage line, so as to guide the robot to move and carry out the corresponding operation. Based on this, an intelligent binocular vision guidance method is proposed in this paper. The image data in the working space is collected by the binocular camera in real time, the wire is identified by the image segmentation technology, the wire is separated from the background, and the spatial pose of the wire is solved by the PNP and binocular stereo vision technology. Through YOLOV5 target detection, the position identification and positioning of the thread and clamp of the drainage line are realized, and the automatic fire ignition operation is finally guided by the manipulator. Experiments show that this method has the advantages of high accuracy, good stability and fast speed.

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.


Optik ◽  
2021 ◽  
pp. 166651
Author(s):  
Lianghui Li ◽  
Jiachen Wang ◽  
Shengli Yang ◽  
Hao Gong

2021 ◽  
Author(s):  
Qingsheng Mu ◽  
Jun Wei ◽  
Zhugang Yuan ◽  
Yuheng Yin

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