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Erschienen in: Neural Computing and Applications 1/2019

09.08.2018 | S.I. : Machine Learning Applications for Self-Organized Wireless Networks

Research on high-resolution improved projection 3D localization algorithm and precision assembly of parts based on virtual reality

verfasst von: Xun Zhang, Guofu Yin, Na Qi

Erschienen in: Neural Computing and Applications | Sonderheft 1/2019

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Abstract

Traditional assembly process design tasks are generally performed manually by experienced craftsmen using 2D drawings, which often require the use of physical prototypes. This kind of assembly process design mode inevitably has the defects of low optimization degree, low design efficiency, and high cost. The current computer-aided assembly process design also has problems such as “combination explosion.” Assembly process design technology and algorithm based on virtual reality and artificial intelligence is an effective way to solve the above problems. The application of the system in a virtual reality system provides an accurate positioning method in a virtual reality system. The ultrasonic three-dimensional space positioning system uses a differential method to improve the ranging accuracy. The system has the advantages of strong anti-electromagnetic interference, insensitivity to light and no electromagnetic radiation; thus, it is suitable for application in virtual reality systems. In the paper, two different methods of assembly process planning are proposed for interactive constraint definition assembly and automatic constraint recognition assembly, which make up for the lack of a single method, make the assembly process more realistic, and realize the assembly path by acquiring sampling points. The recording and playback of the assembly process planning process is achieved using screenshots and video compression techniques.

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Metadaten
Titel
Research on high-resolution improved projection 3D localization algorithm and precision assembly of parts based on virtual reality
verfasst von
Xun Zhang
Guofu Yin
Na Qi
Publikationsdatum
09.08.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe Sonderheft 1/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3665-0

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