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Abstract(s)
A presente dissertação de mestrado foi realizada no seguimento do desenvolvimento de uma solução típica de automação industrial a qual consiste na tarefa de deteção por imagem e captura por um robot industrial, de objetos a serem transportados ao longo de um transportador, sendo a informação do seu posicionamento e orientação recolhida através de uma câmara instalada sobre o transportador.
O projeto recorreu a diversas disciplinas tais como a robótica, visão artificial, e acionamentos eletromecânicos, todos estes a funcionar ligados a um controlador numa topologia de controlo centralizado. Isto levou a um estudo de alguns dos temas que mais têm sofrido evoluções significativas nas últimas décadas e que se propõem a dominar o meio industrial.
Foram analisadas algumas técnicas de processamento de imagem com o objetivo de desenvolver um algoritmo que permitisse detetar algumas características da peça, de modo a capturar a peça na orientação pretendida.
A caracterização do robot utilizado passou pelo estudo dos vários tipos de modelos existentes, de modo a entender melhor os seus meios de aplicação.
Ambos os pontos acima estão bastante presentes em dois temas atuais: Indústria 4.0 e Inteligência artificial. Assim foi feita uma pequena referência ao seu enquadramento na indústria atual.
Utilizou-se também um variador eletrónico de velocidade para controlar o transportador de modo a poder-se adaptar o meio de transporte das peças à captura dos objetos.
Existindo assim vários sistemas isolados com características diferentes e ligados a um mesmo controlador, foi necessário desenvolver interfaces que permitissem a integração de todos numa única solução.
Por último, foi desenvolvido um software completo para ser executado no controlador, colocando todo o sistema em funcionamento conforme descrito. Foi também criado um programa de calibração do sistema de visão o qual permitiu adaptar o funcionamento do anterior ao meio envolvente.
The current Master Thesis was carried out during the development of a typical industrial automation solution, which consists of the task of the image detection and capture by an industrial robot, of objects being transported along a conveyor, with the information of its position taken through a video camera installed above the same conveyor. This project relied on several disciplines such as robotics, artificial vision, and electromechanical drives, all of which are linked to a controller in a centralized control topology. This led to the study of some of the cutting-edge topics that have been under significant evolutions in the last decades, and that aim to be all over the industrial environment. Some image processing techniques were analyzed with the purpose of developing an algorithm that allowed to detect some characteristics of the object, in order to capture it in the desired orientation. The characterization of the robot used, passed through the study of the various existing models, in order to better understand their applications. Both point above are quite present in two quite current topics: Industry 4.0 and Artificial Intelligence. Thus, a small reference was made to its current industry framework. A variable-frequency-drive was also used to control the conveyor so as to be able to adapt the transportation of the object to its capture. With several isolated systems applied, with different characteristics and connected to the same controller, it was also necessary to develop interfaces that allowed to integrate all of them in a single solution. Finally, a complete software was developed to run on the controller, putting the entire system in operation as described. A calibration program was also created, which allowed to adapt the operation of the first program to the surrounding environment.
The current Master Thesis was carried out during the development of a typical industrial automation solution, which consists of the task of the image detection and capture by an industrial robot, of objects being transported along a conveyor, with the information of its position taken through a video camera installed above the same conveyor. This project relied on several disciplines such as robotics, artificial vision, and electromechanical drives, all of which are linked to a controller in a centralized control topology. This led to the study of some of the cutting-edge topics that have been under significant evolutions in the last decades, and that aim to be all over the industrial environment. Some image processing techniques were analyzed with the purpose of developing an algorithm that allowed to detect some characteristics of the object, in order to capture it in the desired orientation. The characterization of the robot used, passed through the study of the various existing models, in order to better understand their applications. Both point above are quite present in two quite current topics: Industry 4.0 and Artificial Intelligence. Thus, a small reference was made to its current industry framework. A variable-frequency-drive was also used to control the conveyor so as to be able to adapt the transportation of the object to its capture. With several isolated systems applied, with different characteristics and connected to the same controller, it was also necessary to develop interfaces that allowed to integrate all of them in a single solution. Finally, a complete software was developed to run on the controller, putting the entire system in operation as described. A calibration program was also created, which allowed to adapt the operation of the first program to the surrounding environment.
Description
Trabalho final de mestrado para obtenção do grau de mestre em Engenharia Eletrotécnica – ramo de Automação e Eletrónica industrial
Keywords
Automação Automation Robótica Robotics Processamento de imagem Image processing Acionamentos eletromecânicos Electromechanical drives Eletrónica industrial Industrial electronics Controlo industrial Industrial control
Citation
COSTA, Jorge Manuel de Figueiredo - Automatização de sistema de separação de peças com recurso a um tapete rolante e um robot e processamento de imagem. Lisboa: Instituto Superior de Engenharia de Lisboa, 2019. Dissertação de mestrado.
Publisher
Instituto Superior de Engenharia de Lisboa