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Conference Paper: Recursive measurement process for improving accuracy of dimensional inspection of automotive body parts

TitleRecursive measurement process for improving accuracy of dimensional inspection of automotive body parts
Authors
Issue Date2007
Citation
Proceedings - IEEE International Conference on Robotics and Automation, 2007, p. 4764-4769 How to Cite?
AbstractAccuracy is essential to surface quality control when a range sensor is applied to measure the 3D shape of an automotive body part. A sensor's viewing pose, including location and orientation, is related to measurement accuracy. It is usually difficult to find an optimal solution by manual control of sensor viewpoints. A CAD-guided robot view planner developed previously can automatically generate viewpoints. Measurement accuracy can be satisfied in a certain range. However, the unpredictable image noises, especially in regions with low intensity contrast, cannot be compensated by the CADguided robot view planner. In another aspect, measurement accuracy is evaluated all over the part surface. The local accuracy of a small patch may exceed the measurement tolerance. In this paper, feedback design is applied to the CADguided robot sensor planning system. The feedback controller can evaluate the accuracy of obtained point clouds, identify problem regions, and generate new viewpoints. This process is recursively executed until the measurement accuracy reaches to a tolerant value. This feedback-based inspection system had been implemented in previous work to fill holes of a point cloud, which are caused by shadows and light reflections. In this paper, the feedback controller is specifically designed to improve the measurement accuracy. Experimental results show the success of applying this feedback system for dimensional inspection of an automotive body part. © 2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/212947
ISSN

 

DC FieldValueLanguage
dc.contributor.authorShi, Quan-
dc.contributor.authorXi, Ning-
dc.contributor.authorSheng, Weihua-
dc.date.accessioned2015-07-28T04:05:32Z-
dc.date.available2015-07-28T04:05:32Z-
dc.date.issued2007-
dc.identifier.citationProceedings - IEEE International Conference on Robotics and Automation, 2007, p. 4764-4769-
dc.identifier.issn1050-4729-
dc.identifier.urihttp://hdl.handle.net/10722/212947-
dc.description.abstractAccuracy is essential to surface quality control when a range sensor is applied to measure the 3D shape of an automotive body part. A sensor's viewing pose, including location and orientation, is related to measurement accuracy. It is usually difficult to find an optimal solution by manual control of sensor viewpoints. A CAD-guided robot view planner developed previously can automatically generate viewpoints. Measurement accuracy can be satisfied in a certain range. However, the unpredictable image noises, especially in regions with low intensity contrast, cannot be compensated by the CADguided robot view planner. In another aspect, measurement accuracy is evaluated all over the part surface. The local accuracy of a small patch may exceed the measurement tolerance. In this paper, feedback design is applied to the CADguided robot sensor planning system. The feedback controller can evaluate the accuracy of obtained point clouds, identify problem regions, and generate new viewpoints. This process is recursively executed until the measurement accuracy reaches to a tolerant value. This feedback-based inspection system had been implemented in previous work to fill holes of a point cloud, which are caused by shadows and light reflections. In this paper, the feedback controller is specifically designed to improve the measurement accuracy. Experimental results show the success of applying this feedback system for dimensional inspection of an automotive body part. © 2007 IEEE.-
dc.languageeng-
dc.relation.ispartofProceedings - IEEE International Conference on Robotics and Automation-
dc.titleRecursive measurement process for improving accuracy of dimensional inspection of automotive body parts-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ROBOT.2007.364213-
dc.identifier.scopuseid_2-s2.0-36348932862-
dc.identifier.spage4764-
dc.identifier.epage4769-

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