DocumentCode :
3715232
Title :
Object recognition in assembly assisted by augmented reality system
Author :
Anderson Nishihara;Jun Okamoto
Author_Institution :
Department of Mechatronics and Mechanical Systems Engineering, Polytechnic School of The University of S?o Paulo, S?o Paulo, Brazil
fYear :
2015
Firstpage :
400
Lastpage :
407
Abstract :
Assembly processes for simple toys or complex machines require instructions to be executed. Traditionally, these instructions are written in the form of paper or digital manuals. These manuals contain descriptive text, photos or diagrams to guide the assembly sequence from the beginning to the final state. To change this paradigm, an augmented reality system is proposed to guide users in assembly tasks. The system recognizes each piece to be assembled through image processing techniques and guides the piece placement with graphic signs. Still, the system checks if the pieces are properly assembled and alerts the user when the assembly has been finished. In the field of assembly assisted by augmented reality systems, many works use some kind of customized device, such as head mounted displays (HMD). Additionally, markers are commonly used to track camera position and to identify assembly parts. These two features restrict the spread of the technology whence, in this work, customized devices and markers to track and identify parts are not used and all the processing is executed on embedded software in an off-the-shelf device without the need of communication with other computers to offload image processing. In this work we present the current results of the proposed system´s object recognition process. The implemented object recognition subsystem is part of a system called A3R (Assembly Assisted by Augmented Reality).
Keywords :
"Assembly","Object recognition","Cameras","Augmented reality","Computers","Manuals","Feature extraction"
Publisher :
ieee
Conference_Titel :
SAI Intelligent Systems Conference (IntelliSys), 2015
Type :
conf
DOI :
10.1109/IntelliSys.2015.7361172
Filename :
7361172
Link To Document :
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