陈海永, 方灶军, 徐德, 孙鹤旭. 基于视觉的薄钢板焊接机器人起始点识别与定位控制[J]. 机器人, 2013, 35(1): 90-97. DOI: 10.3724/SP.J.1218.2013.00090
引用本文: 陈海永, 方灶军, 徐德, 孙鹤旭. 基于视觉的薄钢板焊接机器人起始点识别与定位控制[J]. 机器人, 2013, 35(1): 90-97. DOI: 10.3724/SP.J.1218.2013.00090
CHEN Haiyong, FANG Zaojun, XU De, SUN Hexu. Vision Based Starting Position Recognition and Positioning Controlfor Thin Steel Sheet Welding Robot[J]. ROBOT, 2013, 35(1): 90-97. DOI: 10.3724/SP.J.1218.2013.00090
Citation: CHEN Haiyong, FANG Zaojun, XU De, SUN Hexu. Vision Based Starting Position Recognition and Positioning Controlfor Thin Steel Sheet Welding Robot[J]. ROBOT, 2013, 35(1): 90-97. DOI: 10.3724/SP.J.1218.2013.00090

基于视觉的薄钢板焊接机器人起始点识别与定位控制

Vision Based Starting Position Recognition and Positioning Controlfor Thin Steel Sheet Welding Robot

  • 摘要: 针对集装箱薄钢板对接焊,提出一种新颖的焊接机器人起始点识别和焊枪精确对中焊缝起始点的视觉控制方法.首先提出一种迭代圆形霍夫变换方法,自动确定了包含焊枪特征点的圆形感兴趣区域,第2次迭代可实现焊枪特征点的识别和提取,具有鲁棒性和快速性的优点.接着使用直线霍夫变换方法实现了焊缝直线的识别和焊缝特征点的提取,进而设计了基于图像空间的焊缝起始点视觉控制方案,实现了焊缝起始点的精确定位控制.实验结果表明,提出的方法具有很好的鲁棒性,能够精确地识别出焊枪和焊缝特征坐标.视觉控制法能够快速地将焊枪定位到焊缝起始点位置.集装箱厂现场焊接测试也证实了这些方法的有效性,得到了满意的结果.

     

    Abstract: For the thin steel plate butt welding of containers, a visual control method of welding robot is proposed to recognize starting position and drive the weld torch to accurately track the starting position. Firstly, an iterative circle Hough transformation is presented, which can automatically obtain the region of interest including the torch characteristic point. In the second iteration, the torch characteristic point is recognized and extracted, robustly and quickly. Then the seam is recognized and its characteristic point is extracted by using line Hough transformation. Furthermore, an image space based visual control scheme of starting position is designed, and the accurate starting position control is achieved. The experimental results show that the proposed scheme can extract the torch's and seam's characteristic point coordinates, accurately and robustly. Moreover, the torch can be driven to the starting position quickly and accurately by using the visual control. Finally, test results in the container factory also verify the effectiveness of these methods, and the satisfactory results are obtained.

     

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