• Laser & Optoelectronics Progress
  • Vol. 58, Issue 3, 3120051 (2021)
Li Pengchao1、2、3, Wang Jintao1、2、4、*, Song Jilai1、4, Wang Xiaofeng4, and Xu Fang1、2、4
Author Affiliations
  • 1State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang , Liaoning 110016, China
  • 2Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang , Liaoning 110169, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
  • 4Shenyang SIASUN Robot & Automation Co., LTD., Shenyang , Liaoning 110168, China
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    DOI: 10.3788/LOP202158.0312005 Cite this Article Set citation alerts
    Li Pengchao, Wang Jintao, Song Jilai, Wang Xiaofeng, Xu Fang. Weld Recognition of Complex Curved Surface Based on Linear Structured Light Scanning[J]. Laser & Optoelectronics Progress, 2021, 58(3): 3120051 Copy Citation Text show less

    Abstract

    Aiming at the recognition problem of robot adaptive grinding curved surface welding area, an algorithm based on linear structured light for automatic recognition of starting and ending points of grinding robot and a depth image enhancement operator are proposed in this work. The enhancement operator takes the sum of the absolute value of the intensity difference between the center pixel and the pixels in the 8 neighboring regions as the value of the center pixel to enhance the visualization features of the depth image and reveal the texture features of the polished area. First, the point cloud data is filtered and the hole filling is processed; second, the standard deviation of each scan line point cloud in the height direction is calculated; finally, the obtained features are identified to find the position with large feature change in a certain range, so as to extract the area that needs grinding. Experimental results show that the enhancement operator has excellent effect on depth image enhancement, and the average recognition accuracy of the algorithm for the start and end positions is less than 1 mm, which can achieve pixel level accuracy, and has strong robustness and is insensitive to noise. The effectiveness and feasibility of the algorithm are also verified in the field test.
    Li Pengchao, Wang Jintao, Song Jilai, Wang Xiaofeng, Xu Fang. Weld Recognition of Complex Curved Surface Based on Linear Structured Light Scanning[J]. Laser & Optoelectronics Progress, 2021, 58(3): 3120051
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