基于增强现实的产品质量信息传递方法
|
摘要
针对当前工作人员通过二维图纸或者三维CAD模型来检测零件时存在的效率低下等问题,提出一种基于增强现实的产品质量信息传递方法.首先以制造特征为基本载体提取三维CAD模型的产品质量信息;然后离线生成待测模型的多视角模板图像集,并建立模板图像与制造特征之间的关联关系;最后根据摄像机获取的制造现场实时图像建立实时图像与模板图像之间的匹配关系,并根据匹配模板图像的关联信息初始化相机姿态,利用此姿态实现产品质量信息在真实制造现场场景中的叠加.实验结果表明,该方法可以有效地实现产品质量信息在制造现场的传递,提高产品的质量检测效率和减轻工作人员的负担.
To address the problem of low efficiency in product quality checking by using the 2D drawing or 3D model, a product manufacturing information transmission method based on augmented reality is proposed. First, 3D model product manufacturing information is extracted based on manufacturing features.Then, the multi-view template image set of the inspecting 3D CAD model is generated in the offline stage and the correlation between the template image and the manufacturing feature is established. Finally, according to the real-time images obtained by the camera, the matching relationship between the real-time images and the template images is established, and the camera pose is initialized according to the correlation information of the matching template images. The product manufacturing information is augmented onto the manufacturing site image by using this initial pose. The results of the experiments show that the method can effectively transfer the product manufacturing information in the manufacturing site, improve the efficiency of product quality inspecting, and lighten the burden of staffs.
To address the problem of low efficiency in product quality checking by using the 2D drawing or 3D model, a product manufacturing information transmission method based on augmented reality is proposed. First, 3D model product manufacturing information is extracted based on manufacturing features.Then, the multi-view template image set of the inspecting 3D CAD model is generated in the offline stage and the correlation between the template image and the manufacturing feature is established. Finally, according to the real-time images obtained by the camera, the matching relationship between the real-time images and the template images is established, and the camera pose is initialized according to the correlation information of the matching template images. The product manufacturing information is augmented onto the manufacturing site image by using this initial pose. The results of the experiments show that the method can effectively transfer the product manufacturing information in the manufacturing site, improve the efficiency of product quality inspecting, and lighten the burden of staffs.
引文
[1]Quintana V,Rivest L,Pellerin R,et al.Will model-based definition replace engineering drawings throughout the product lifecycle?A global perspective from aerospace industry[J].Computers in Industry,2010,61(5):497-508
[2]Alemanni M,Destefanis F,Vezzetti E.Model-based definition design in the product lifecycle management scenario[J].The International Journal of Advanced Manufacturing Technology,2011,52(1-4):1-14
[3]Liestol G,Morrison A.Views,alignment and incongruity in indirect augmented reality[C]//Proceedings of the IEEE International Symposium on Mixed and Augmented Reality-Arts,Media and Humanities.Los Alamitos:IEEE Computer Society Press,2013:23-28
[4]Palmarini R,Erkoyuncu J A,Roy R,et al.A systematic review of augmented reality applications in maintenance[J].Robotics and Computer-Integrated Manufacturing,2017,49:215-228
[5]Han P F,Zhao G.CAD-based 3D objects recognition in monocular images for mobile augmented reality[J].Computers&Graphics,2015,50:36-46
[6]Kim D,Park J,Ko K H.Development of an AR based method for augmentation of 3D CAD data onto a real ship block image[J].Computer-Aided Design,2018,98:1-11
[7]Marchandé,Bouthemy P,Chaumette F.A 2D-3D model-based approach to real-time visual tracking[J].Image and Vision Computing,2001,19(13):941-955
[8]Hinterstoisser S,Cagniart C,Ilic S,et al.Gradient response maps for real-time detection of textureless objects[J].IEEETransactions on Pattern Analysis and Machine Intelligence,2012,34(5):876-888
[9]Zhu W J,Wang P,Li R,et al.Real-time 3D work-piece tracking with monocular camera based on static and dynamic model libraries[J].Assembly Automation,2017,37(2):219-229
[10]Belkin N J.Cognitive models and information transfer[J].Social Science Information Studies,1984,4(2/3):111-129
[11]Huang Rui,Zhang Shusheng,Bai Xiaoliang.Manufacturability driven interacting machining feature recognition algorithms for3D CAD models[J].Journal of Computer Aided Design&Computer Graphics,2013,25(7):1089-1098(in Chinese)(黄瑞,张树生,白晓亮.可制造性驱动的三维CAD模型相交制造特征识别方法[J].计算机辅助设计与图形学学报,2013,25(7):1089-1098)
[12]Hinterstoisser S,Lepetit V,Ilic S,et al.Model based training,detection and pose estimation of texture-less 3D objects in heavily cluttered scenes[C]//Proceedings of the 11th Asian Conference on Computer Vision.Heidelberg:Springer,2012,7724:548-562
[13]Hinterstoisser S,Holzer S,Cagniart C,et al.Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes[C]//Proceedings of the IEEE International Conference on Computer Vision.Los Alamitos:IEEE Computer Society Press,2012:858-865
[14]Abawi D F,Bienwald J,Dorner R.Accuracy in optical tracking with fiducial markers:an accuracy function for ARTool Kit[C]//Proceedings of the 3rd IEEE and ACM International Symposium on Mixed and Augmented Reality.Los Alamitos:IEEEComputer Society,2004:260-261
[2]Alemanni M,Destefanis F,Vezzetti E.Model-based definition design in the product lifecycle management scenario[J].The International Journal of Advanced Manufacturing Technology,2011,52(1-4):1-14
[3]Liestol G,Morrison A.Views,alignment and incongruity in indirect augmented reality[C]//Proceedings of the IEEE International Symposium on Mixed and Augmented Reality-Arts,Media and Humanities.Los Alamitos:IEEE Computer Society Press,2013:23-28
[4]Palmarini R,Erkoyuncu J A,Roy R,et al.A systematic review of augmented reality applications in maintenance[J].Robotics and Computer-Integrated Manufacturing,2017,49:215-228
[5]Han P F,Zhao G.CAD-based 3D objects recognition in monocular images for mobile augmented reality[J].Computers&Graphics,2015,50:36-46
[6]Kim D,Park J,Ko K H.Development of an AR based method for augmentation of 3D CAD data onto a real ship block image[J].Computer-Aided Design,2018,98:1-11
[7]Marchandé,Bouthemy P,Chaumette F.A 2D-3D model-based approach to real-time visual tracking[J].Image and Vision Computing,2001,19(13):941-955
[8]Hinterstoisser S,Cagniart C,Ilic S,et al.Gradient response maps for real-time detection of textureless objects[J].IEEETransactions on Pattern Analysis and Machine Intelligence,2012,34(5):876-888
[9]Zhu W J,Wang P,Li R,et al.Real-time 3D work-piece tracking with monocular camera based on static and dynamic model libraries[J].Assembly Automation,2017,37(2):219-229
[10]Belkin N J.Cognitive models and information transfer[J].Social Science Information Studies,1984,4(2/3):111-129
[11]Huang Rui,Zhang Shusheng,Bai Xiaoliang.Manufacturability driven interacting machining feature recognition algorithms for3D CAD models[J].Journal of Computer Aided Design&Computer Graphics,2013,25(7):1089-1098(in Chinese)(黄瑞,张树生,白晓亮.可制造性驱动的三维CAD模型相交制造特征识别方法[J].计算机辅助设计与图形学学报,2013,25(7):1089-1098)
[12]Hinterstoisser S,Lepetit V,Ilic S,et al.Model based training,detection and pose estimation of texture-less 3D objects in heavily cluttered scenes[C]//Proceedings of the 11th Asian Conference on Computer Vision.Heidelberg:Springer,2012,7724:548-562
[13]Hinterstoisser S,Holzer S,Cagniart C,et al.Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes[C]//Proceedings of the IEEE International Conference on Computer Vision.Los Alamitos:IEEE Computer Society Press,2012:858-865
[14]Abawi D F,Bienwald J,Dorner R.Accuracy in optical tracking with fiducial markers:an accuracy function for ARTool Kit[C]//Proceedings of the 3rd IEEE and ACM International Symposium on Mixed and Augmented Reality.Los Alamitos:IEEEComputer Society,2004:260-261