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GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning

Automatic robot gripper system which involves the automated object recognition of work-in-process in production line is the key technology of the upcoming manufacturing facility achieving Industry 4.0. Automatic robot gripper enables the manufacturing system to be autonomous, self-recognized, and ad...

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Detalles Bibliográficos
Autores principales: Park, JoungMin, Lee, SangYoon, Lee, JaeWoon, Um, Jumyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662704/
https://www.ncbi.nlm.nih.gov/pubmed/33143047
http://dx.doi.org/10.3390/s20216183
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author Park, JoungMin
Lee, SangYoon
Lee, JaeWoon
Um, Jumyung
author_facet Park, JoungMin
Lee, SangYoon
Lee, JaeWoon
Um, Jumyung
author_sort Park, JoungMin
collection PubMed
description Automatic robot gripper system which involves the automated object recognition of work-in-process in production line is the key technology of the upcoming manufacturing facility achieving Industry 4.0. Automatic robot gripper enables the manufacturing system to be autonomous, self-recognized, and adaptable by using artificial intelligence of robot programming dealing with arbitrary shapes of work-in-processes. This paper specifically explores the chain of key technologies, such as 3D object recognition with CAD and point cloud data, reinforcement learning of robot arm, and customized 3D printed gripper, in order to enhance the intelligence of the robot controller system. And it also proposes the integration with 3D point cloud based object recognition and game-engine based reinforcement learning. The result of the prototype of the intelligent robot gripping system developed by the proposed method with a 4 degree-of-freedom robot arm is explained in this paper.
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spelling pubmed-76627042020-11-14 GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning Park, JoungMin Lee, SangYoon Lee, JaeWoon Um, Jumyung Sensors (Basel) Article Automatic robot gripper system which involves the automated object recognition of work-in-process in production line is the key technology of the upcoming manufacturing facility achieving Industry 4.0. Automatic robot gripper enables the manufacturing system to be autonomous, self-recognized, and adaptable by using artificial intelligence of robot programming dealing with arbitrary shapes of work-in-processes. This paper specifically explores the chain of key technologies, such as 3D object recognition with CAD and point cloud data, reinforcement learning of robot arm, and customized 3D printed gripper, in order to enhance the intelligence of the robot controller system. And it also proposes the integration with 3D point cloud based object recognition and game-engine based reinforcement learning. The result of the prototype of the intelligent robot gripping system developed by the proposed method with a 4 degree-of-freedom robot arm is explained in this paper. MDPI 2020-10-30 /pmc/articles/PMC7662704/ /pubmed/33143047 http://dx.doi.org/10.3390/s20216183 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Park, JoungMin
Lee, SangYoon
Lee, JaeWoon
Um, Jumyung
GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning
title GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning
title_full GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning
title_fullStr GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning
title_full_unstemmed GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning
title_short GadgetArm—Automatic Grasp Generation and Manipulation of 4-DOF Robot Arm for Arbitrary Objects Through Reinforcement Learning
title_sort gadgetarm—automatic grasp generation and manipulation of 4-dof robot arm for arbitrary objects through reinforcement learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662704/
https://www.ncbi.nlm.nih.gov/pubmed/33143047
http://dx.doi.org/10.3390/s20216183
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