Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor

Detalhes bibliográficos
Autor(a) principal: Moreira,E
Data de Publicação: 2016
Outros Autores: Luís Freitas Rocha, Andry Maykol Pinto, António Paulo Moreira, Germano Veiga
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/4984
http://dx.doi.org/10.1109/LRA.2016.2524043
Resumo: This letter presents a novel architecture for evaluating the success of picking operations that are executed by industrial robots. It is formed by a cascade of machine learning algorithms (kNN and SVM) and uses information obtained by a 6 axis force/torque sensor and, if available, information from the built-in sensors of the robotic gripper. Beyond measuring the success or failure of the entire operation, this architecture makes it possible to detect in real-time when an object is slipping during the picking. Therefore, force and torque signatures are collected during the picking movement of the robot, which is decomposed into five different stages that allows to characterize distinct levels of success over time. Several trials were performed using an industrial robot with two different grippers for picking a long and flexible object. The experiments demonstrate the reliability of the proposed approach under different picking scenarios since, it obtained a testing performance (in terms of accuracy) up to 99.5% of successful identification of the result of the picking operations, considering an universe of 400 attempts. © 2016 IEEE.
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spelling Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque SensorThis letter presents a novel architecture for evaluating the success of picking operations that are executed by industrial robots. It is formed by a cascade of machine learning algorithms (kNN and SVM) and uses information obtained by a 6 axis force/torque sensor and, if available, information from the built-in sensors of the robotic gripper. Beyond measuring the success or failure of the entire operation, this architecture makes it possible to detect in real-time when an object is slipping during the picking. Therefore, force and torque signatures are collected during the picking movement of the robot, which is decomposed into five different stages that allows to characterize distinct levels of success over time. Several trials were performed using an industrial robot with two different grippers for picking a long and flexible object. The experiments demonstrate the reliability of the proposed approach under different picking scenarios since, it obtained a testing performance (in terms of accuracy) up to 99.5% of successful identification of the result of the picking operations, considering an universe of 400 attempts. © 2016 IEEE.2017-12-27T16:26:02Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4984http://dx.doi.org/10.1109/LRA.2016.2524043engMoreira,ELuís Freitas RochaAndry Maykol PintoAntónio Paulo MoreiraGermano Veigainfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:21Zoai:repositorio.inesctec.pt:123456789/4984Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:00.588318Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
title Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
spellingShingle Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
Moreira,E
title_short Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
title_full Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
title_fullStr Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
title_full_unstemmed Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
title_sort Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
author Moreira,E
author_facet Moreira,E
Luís Freitas Rocha
Andry Maykol Pinto
António Paulo Moreira
Germano Veiga
author_role author
author2 Luís Freitas Rocha
Andry Maykol Pinto
António Paulo Moreira
Germano Veiga
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Moreira,E
Luís Freitas Rocha
Andry Maykol Pinto
António Paulo Moreira
Germano Veiga
description This letter presents a novel architecture for evaluating the success of picking operations that are executed by industrial robots. It is formed by a cascade of machine learning algorithms (kNN and SVM) and uses information obtained by a 6 axis force/torque sensor and, if available, information from the built-in sensors of the robotic gripper. Beyond measuring the success or failure of the entire operation, this architecture makes it possible to detect in real-time when an object is slipping during the picking. Therefore, force and torque signatures are collected during the picking movement of the robot, which is decomposed into five different stages that allows to characterize distinct levels of success over time. Several trials were performed using an industrial robot with two different grippers for picking a long and flexible object. The experiments demonstrate the reliability of the proposed approach under different picking scenarios since, it obtained a testing performance (in terms of accuracy) up to 99.5% of successful identification of the result of the picking operations, considering an universe of 400 attempts. © 2016 IEEE.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-01T00:00:00Z
2016
2017-12-27T16:26:02Z
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http://dx.doi.org/10.1109/LRA.2016.2524043
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