纺织学报 ›› 2017, Vol. 38 ›› Issue (08): 156-160.doi: 10.13475/j.fzxb.20160801505

• 管理与信息化 • 上一篇    下一篇

采用双目视觉的织物曲面接缝提取与缝合路径规划

  

  • 收稿日期:2016-08-08 修回日期:2017-05-04 出版日期:2017-08-15 发布日期:2017-08-10

Fabric curved surface seam extraction using binocular vision and stitching path planning

  • Received:2016-08-08 Revised:2017-05-04 Online:2017-08-15 Published:2017-08-10

摘要:

针对曲面织物的接缝自动提取及缝合路径规划问题,提出一种基于双目视觉的接缝自动识别方法。结合缝合预制件的三维点云与二维图像之间的空间位置转换关系,得到预制件二维图像中接缝在三维点云中的映射;进一步采用基于弗莱纳雪列矢量的路径规划方法,对缝合路径上各位置的弗莱纳雪列(Frenet-Serret)矢量进行计算,求出机器人末端执行器的位姿,利用MatLab 对机器人的缝合路径进行仿真。实验结果表明:该方法能够精确快速地对接缝的空间位置进行定位,解决了自动缝合过程中缝合路径寻找困难、精度不高等问题,并可快速地对机器人缝合路径进行规划。

关键词: 曲面织物, 双目视觉, 接缝位置, 弗莱纳雪列矢量, 缝合路径规划

Abstract:

Aiming at the seam automatic extraction and the stitching path planning of curve surface fabrics, a seam automatic recognition method based on binocular vision was proposed. Combined the spatial position conversion between three dimensional points cloud and the two dimensional image of a stitched prefabricated part, the map of the seam in two dimensional image of the prefabricated paart in the three dimensional points cloud was acquired. Furthermore, Freenet-Serret vectors in all positions of the stitching path were calculated by a path designing method based on Frenet-Serret vectors, the posture of a robot terminal was calculated, and the stitching path of the robot was simulated using MatLab. The experimental results show that the method can position the spatial positions of a seam accurately and quickly and solve the problems in the automatic stitching process on difficut stitching path search and low precision, and can also plan a stitching path of the robot quickly.

Key words: curve surface fabric, binocular vision, seam position, Frenet-Serret vector, stitching path planning

[1] 陈益松 夏明. 光学三角测量法及其在人体测量中的应用[J]. 纺织学报, 2012, 33(12): 95-101.
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