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Optimization of Abnormal Point Cloud Recognition in Robot Vision Grinding System Based on Multidimensional Improved Eigenvalue Method (MIEM)
Joint Authors
Li, Guanglei
Cui, Yahui
Wang, Lihua
Meng, Lei
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-22
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
To improve the accurate and sufficient recognition of abnormal points on the workpiece, a multidimensional anomaly point identification approach based on an improved eigenvalue method is proposed in this paper.
Whether a point is normal or not depends on the angle between the two adjacent vectors which consisted of four adjacent points around the current focus.
The comprehensive judgment is carried out by multidimensional approximation.
The numerical simulation and actual experiment validate the efficiency of the proposed method to quickly and accurately identify the abnormal point cloud in the surface point cloud data.
American Psychological Association (APA)
Li, Guanglei& Cui, Yahui& Wang, Lihua& Meng, Lei. 2020. Optimization of Abnormal Point Cloud Recognition in Robot Vision Grinding System Based on Multidimensional Improved Eigenvalue Method (MIEM). Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1195345
Modern Language Association (MLA)
Li, Guanglei…[et al.]. Optimization of Abnormal Point Cloud Recognition in Robot Vision Grinding System Based on Multidimensional Improved Eigenvalue Method (MIEM). Mathematical Problems in Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1195345
American Medical Association (AMA)
Li, Guanglei& Cui, Yahui& Wang, Lihua& Meng, Lei. Optimization of Abnormal Point Cloud Recognition in Robot Vision Grinding System Based on Multidimensional Improved Eigenvalue Method (MIEM). Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1195345
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195345