scholarly journals Application of three-dimensional vision perception technology to industrial robots

2021 ◽  
Vol 2082 (1) ◽  
pp. 012002
Author(s):  
Rui Yang ◽  
Qinglong Mo ◽  
Yuhong Li ◽  
Lin Gan ◽  
Ruihan Hu

Abstract The three-dimensional vision system can improve the active perception ability of the robot, and then guide its flexible operation. This system has been widely used in industrial production processes, such as disorderly sorting, assembly, flexible welding, and defect detection. In sorting, assembly and other applications, accurate perception in a complex and changeable industrial environment is essential. Moreover, the control and other operations should be completed under the guidance of feedback information based on the collected three-dimensional perception results. Nonetheless, improvements are still required, such as accurate three-dimensional detection and positioning of work-in-progress and autonomous guidance in a complicated industrial context with continuous changes.

1989 ◽  
Author(s):  
Keiichi Kemmotsu ◽  
Yuichi Sasano ◽  
Katsumi Oshitani

Author(s):  
Philips S Ogun ◽  
Matthew R Chamberlain ◽  
Punnu L Phairatt ◽  
Mitulkumar J Tailor ◽  
Michael R Jackson

2002 ◽  
Author(s):  
Valentin E. Tyrsa ◽  
Larisa P. Burtseva ◽  
Vera Tyrsa ◽  
Ivan Kalaykov ◽  
Anani Ananiev

2013 ◽  
Vol 199 ◽  
pp. 235-240 ◽  
Author(s):  
Andrzej Sioma

This article is devoted to the methods of image analysis used in three-dimensional vision systems. Based on a sample set of 3D images, their defects resulting from the adopted three-dimensional image construction technique are discussed. Those defects are discussed in relation to the following parameters: speed of the vision system, power of the laser, laser mode, laser arrangement relative to the vision system sensor and relative to the tested surface. To illustrate the cases discussed, images showing the effects of selected parameters on the quality of mapping of the tested object onto a three-dimensional image were presented. The next part of the article discusses methods of range image filtering that removes or reduces the importance of defects of the adopted method in any control and measuring tasks. Particular attention is given to methods of removing data described as missing data.


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