Category classification of deformable object using hybrid dynamic model for robotic grasping
Agricultural robots; Clothes; Convolutional neural networks; Deep neural networks; Deformation; Dynamic models; Object recognition; Simulation platform; Category Classification; Deformable object; Home service robot; Hybrid dynamic modeling; Off-line simulations; Robotic manipulation; Unfolding proc...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-244562023-05-29T15:23:40Z Category classification of deformable object using hybrid dynamic model for robotic grasping Hou Y.C. Sahari K.S.M. How D.N.T. Weng L.Y. 37067465000 57218170038 57212923888 26326032700 Agricultural robots; Clothes; Convolutional neural networks; Deep neural networks; Deformation; Dynamic models; Object recognition; Simulation platform; Category Classification; Deformable object; Home service robot; Hybrid dynamic modeling; Off-line simulations; Robotic manipulation; Unfolding procedures; Visual identification; Robotics This work studies the problem of classification of a hung garment in the unfolding procedure by a home service robot. The sheer number of unpredictable configurations that the deformable object can end up in makes the visual identification of the object shape and size difficult. In this paper, we propose a hybrid dynamic model to recognize the pose of hung garment using a single manipulator. A dataset of hung garment is generated by capturing the depth images of real garments at the robotic platform (real images) and also the images of garment mesh model from offline simulation (synthetic images) respectively. Deep convolutional neural network is implemented to classify the category and estimate the pose of garment. Experiment results show that the proposed method performs well and is applicable to different garments in robotic manipulation. � 2019 IEEE. Final 2023-05-29T07:23:39Z 2023-05-29T07:23:39Z 2019 Conference Paper 10.1109/CRC.2019.00021 2-s2.0-85084042877 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084042877&doi=10.1109%2fCRC.2019.00021&partnerID=40&md5=6c289a98e51910d4a5ad1a8a3f1e2c81 https://irepository.uniten.edu.my/handle/123456789/24456 9058831 57 64 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Agricultural robots; Clothes; Convolutional neural networks; Deep neural networks; Deformation; Dynamic models; Object recognition; Simulation platform; Category Classification; Deformable object; Home service robot; Hybrid dynamic modeling; Off-line simulations; Robotic manipulation; Unfolding procedures; Visual identification; Robotics |
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37067465000 |
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37067465000 Hou Y.C. Sahari K.S.M. How D.N.T. Weng L.Y. |
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Conference Paper |
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Hou Y.C. Sahari K.S.M. How D.N.T. Weng L.Y. |
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Hou Y.C. Sahari K.S.M. How D.N.T. Weng L.Y. Category classification of deformable object using hybrid dynamic model for robotic grasping |
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Hou Y.C. |
title |
Category classification of deformable object using hybrid dynamic model for robotic grasping |
title_short |
Category classification of deformable object using hybrid dynamic model for robotic grasping |
title_full |
Category classification of deformable object using hybrid dynamic model for robotic grasping |
title_fullStr |
Category classification of deformable object using hybrid dynamic model for robotic grasping |
title_full_unstemmed |
Category classification of deformable object using hybrid dynamic model for robotic grasping |
title_sort |
category classification of deformable object using hybrid dynamic model for robotic grasping |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2023 |
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1806425978040221696 |
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13.211869 |