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Conference Paper Dynamic Object Recognition Using Precise Location Detection and ANN for Robot Manipulator
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Authors
Kye Kyung Kim, Jaemin Cho, Pyo Ji Hyung, Kang Sang Seung, 김진호
Issue Date
201705
Source
International Conference on Control, Artificial Intelligence, Robotics and Optimization (ICCAIRO) 2017, pp.237-241
DOI
https://dx.doi.org/10.1109/ICCAIRO.2017.52
Project Code
17PS1300, Next Generation Manufacturing Robot for Smart Factory and Work-Space Sharing with Human, Kang Sang Seung
Abstract
This paper presents vision based dynamic object recognition system for robot manipulation tasks by increasing the needs of automation machine vision. Object recognition or localization technology is used for pick and place task using robot. The dynamic object recognition system detects landmark features using neural network and provides grasping points of randomly located object, bin-picking object, visual servoing object to robot. The characteristic of dynamic object is free of posture, location, shape, distance, stacked form and is not restricted in illumination condition. This paper uses neural network based feature extractor and object classifier to recognize dynamic object. Dynamic object recognition system goes through image processing less impact to illumination effect, landmark feature extraction according to an object, coupled NN based object detection and recognition. We have evaluated performance of dynamic object recognition by testing detection of location, estimation of posture, distance to object and by identifying object type. And the other performance has evaluated by processing pick and place task using robot manipulator.
KSP Keywords
Bin-picking, Feature extractioN, Illumination conditions, Illumination effect, Image processing, Located object, Object Detection and Recognition, Pick and Place, Precise location, Robot manipulation, Robot manipulator