Precision bin-picking using a 3D sensor and a 1D laser sensor
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/27012 |
Resumo: | The technique that is being used by a robot to grab objects that are randomly placed inside a box or on a pallet is called bin-picking. This process is of great interest in an industrial environment as it provides enhanced automation, increased production and cost reduction. Bin-picking has evolved greatly over the years due to tremendous strides empowered by advanced vision technology, software, and gripping solutions which are in constant development. However, the creation of a versatile system, capable of collecting any type of object without deforming it, regardless of the disordered environment around it, remains a challenge. To this goal, the use of 3D perception is unavoidable. Still, the information acquired by some lower cost 3D sensors is not very precise; therefore, the combination of this information with the one of other devices is an approach already in study. The main goal of this work is to develop a solution for the execution of a precise bin-picking process capable of grasping small and fragile objects without breaking or deforming them. This may be done by combining the information provided by two sensors: one 3D sensor (Kinect) used to analyse the workspace and identify the object, and a 1D laser sensor to determine the exact distance to the object when approaching it. Additionally, the developed system may be placed at the end of a manipulator in order to become an active perception unit. Once the global system of sensors, their controllers and the robotic manipulator are integrated into a ROS (Robot Operating System) infrastructure, the data provided by the sensors can be analysed and combined to provide a bin-picking solution. Finally, the testing phase demonstrated the viability and the reliability of the developed bin-picking process. |
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Precision bin-picking using a 3D sensor and a 1D laser sensorBin-pickingFanuc LR Mate 200iDKinect SensorLaser SensorROSROSIndustrialMoveItPoint CloudPCLPrecisionThe technique that is being used by a robot to grab objects that are randomly placed inside a box or on a pallet is called bin-picking. This process is of great interest in an industrial environment as it provides enhanced automation, increased production and cost reduction. Bin-picking has evolved greatly over the years due to tremendous strides empowered by advanced vision technology, software, and gripping solutions which are in constant development. However, the creation of a versatile system, capable of collecting any type of object without deforming it, regardless of the disordered environment around it, remains a challenge. To this goal, the use of 3D perception is unavoidable. Still, the information acquired by some lower cost 3D sensors is not very precise; therefore, the combination of this information with the one of other devices is an approach already in study. The main goal of this work is to develop a solution for the execution of a precise bin-picking process capable of grasping small and fragile objects without breaking or deforming them. This may be done by combining the information provided by two sensors: one 3D sensor (Kinect) used to analyse the workspace and identify the object, and a 1D laser sensor to determine the exact distance to the object when approaching it. Additionally, the developed system may be placed at the end of a manipulator in order to become an active perception unit. Once the global system of sensors, their controllers and the robotic manipulator are integrated into a ROS (Robot Operating System) infrastructure, the data provided by the sensors can be analysed and combined to provide a bin-picking solution. Finally, the testing phase demonstrated the viability and the reliability of the developed bin-picking process.À tecnologia usada por um robô para agarrar objetos que estão dispostos de forma aleatória dentro de uma caixa ou sobre uma palete chama-se binpicking. Este processo é de grande interesse para a industria uma vez que oferece maior autonomia, aumento de produção e redução de custos. O binpicking tem evoluido de forma significativa ao longo dos anos graças aos avanços possibilitados pelo desenvolvimento tecnológico na área da visão, software e soluções de diferentes garras que estão em constante evolução. Contudo, a criação de um sistema versátil, capaz de agarrar qualquer tipo de objeto sem o deformar, independentemente do ambiente desordenado à sua volta, continua a ser o principal objetivo. Para esse fim, o recurso à perceção 3D é imprescindível. Ainda assim, a informação adquirida por sensores 3D não é muito precisa e, por isso, a combinação deste com a de outros dispositivos é uma abordagem ainda em estudo. O objetivo principal deste trabalho é então desenvolver uma solução para a execução de um processo de bin-picking capaz de agarrar objetos pequenos e frágeis sem os partir ou deformar. Isto poderá ser feito através da combinação entre a informação proveniente de dois sensores: um sensor 3D (Kinect) usado para analisar o espaço de trabalho e identificar o objeto, e um sensor laser 1D usado para determinar a sua distância exata e assim se poder aproximar. Adicionalmente, o sistema desenvolvido pode ser acoplado a um manipulador de forma a criar uma unidade de perceção ativa. Uma vez tendo um sistema global de sensores, os seus controladores e o manipulador robótico integrados numa infraestrutura ROS (Robot Operating System), os dados fornecidos pelos sensores podem ser analisados e combinados, e uma solução de bin-picking pode ser desenvolvida. Por último, a fase de testes demonstrou, depois de alguns ajustes nas medidas do sensor laser, a viabilidade e fiabilidade do processo de bin-picking desenvolvido.2019-11-23T14:48:57Z2018-09-26T00:00:00Z2018-09-26info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/27012TID:202237818engMota, Joana Beatriz Carvalhoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T11:52:21Zoai:ria.ua.pt:10773/27012Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:59:54.275581Repositório 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 |
Precision bin-picking using a 3D sensor and a 1D laser sensor |
title |
Precision bin-picking using a 3D sensor and a 1D laser sensor |
spellingShingle |
Precision bin-picking using a 3D sensor and a 1D laser sensor Mota, Joana Beatriz Carvalho Bin-picking Fanuc LR Mate 200iD Kinect Sensor Laser Sensor ROS ROSIndustrial MoveIt Point Cloud PCL Precision |
title_short |
Precision bin-picking using a 3D sensor and a 1D laser sensor |
title_full |
Precision bin-picking using a 3D sensor and a 1D laser sensor |
title_fullStr |
Precision bin-picking using a 3D sensor and a 1D laser sensor |
title_full_unstemmed |
Precision bin-picking using a 3D sensor and a 1D laser sensor |
title_sort |
Precision bin-picking using a 3D sensor and a 1D laser sensor |
author |
Mota, Joana Beatriz Carvalho |
author_facet |
Mota, Joana Beatriz Carvalho |
author_role |
author |
dc.contributor.author.fl_str_mv |
Mota, Joana Beatriz Carvalho |
dc.subject.por.fl_str_mv |
Bin-picking Fanuc LR Mate 200iD Kinect Sensor Laser Sensor ROS ROSIndustrial MoveIt Point Cloud PCL Precision |
topic |
Bin-picking Fanuc LR Mate 200iD Kinect Sensor Laser Sensor ROS ROSIndustrial MoveIt Point Cloud PCL Precision |
description |
The technique that is being used by a robot to grab objects that are randomly placed inside a box or on a pallet is called bin-picking. This process is of great interest in an industrial environment as it provides enhanced automation, increased production and cost reduction. Bin-picking has evolved greatly over the years due to tremendous strides empowered by advanced vision technology, software, and gripping solutions which are in constant development. However, the creation of a versatile system, capable of collecting any type of object without deforming it, regardless of the disordered environment around it, remains a challenge. To this goal, the use of 3D perception is unavoidable. Still, the information acquired by some lower cost 3D sensors is not very precise; therefore, the combination of this information with the one of other devices is an approach already in study. The main goal of this work is to develop a solution for the execution of a precise bin-picking process capable of grasping small and fragile objects without breaking or deforming them. This may be done by combining the information provided by two sensors: one 3D sensor (Kinect) used to analyse the workspace and identify the object, and a 1D laser sensor to determine the exact distance to the object when approaching it. Additionally, the developed system may be placed at the end of a manipulator in order to become an active perception unit. Once the global system of sensors, their controllers and the robotic manipulator are integrated into a ROS (Robot Operating System) infrastructure, the data provided by the sensors can be analysed and combined to provide a bin-picking solution. Finally, the testing phase demonstrated the viability and the reliability of the developed bin-picking process. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-09-26T00:00:00Z 2018-09-26 2019-11-23T14:48:57Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/27012 TID:202237818 |
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http://hdl.handle.net/10773/27012 |
identifier_str_mv |
TID:202237818 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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