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Multi-objects detection and classification using Vision Builder for autonomous assembly

Pattaraporn Taptimtong, Chowarit Mitsantisuk, Kanyakorn Sripattanaon, Chayanit Duangkaew, Nichakul Pewleungsawat

Year
2019
Citations
2

Abstract

in this paper, we proposed the methods of object detection and object classification to obtain the location information of each objects on the placement mat through the state diagram process using Vision Builder for Automated inspection (AI). By using the state diagram design detect and classify object on placement mat found that the state diagram can detect and classify almost it objects, both objects with similar surface pattern and objects with similar size. The location of the objects data can be detected and classified have the accuracy is about ±0.5 millimeter. And after using this object's location data with the automation system, it was found that the robot moved to the position of the object correctly and was able to pick the object for assembly.

Keywords

Artificial intelligenceObject (grammar)Computer visionComputer scienceState diagramObject detectionProcess (computing)State (computer science)AutomationMachine vision

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