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Detalhes

Detalhes

014
Publicações

2020

Detecting and Solving Tube Entanglement in Bin Picking Operations

Autores
Leao, G; Costa, CM; Sousa, A; Veiga, G;

Publicação
Applied Sciences

Abstract
Manufacturing and production industries are increasingly turning to robots to carry out repetitive picking operations in an efficient manner. This paper focuses on tackling the novel challenge of automating the bin picking process for entangled objects, for which there is very little research. The chosen case study are sets of freely curved tubes, which are prone to occlusions and entanglement. The proposed algorithm builds a representation of the tubes as an ordered list of cylinders and joints using a point cloud acquired by a 3D scanner. This representation enables the detection of occlusions in the tubes. The solution also performs grasp planning and motion planning, by evaluating post-grasp trajectories via simulation using Gazebo and the ODE physics engine. A force/torque sensor is used to determine how many items were picked by a robot gripper and in which direction it should rotate to solve cases of entanglement. Real-life experiments with sets of PVC tubes and rubber radiator hoses showed that the robot was able to pick a single tube on the first try with success rates of 99% and 93%, respectively. This study indicates that using simulation for motion planning is a promising solution to deal with entangled objects.

2020

Optimal automatic path planner and design for high redundancy robotic systems

Autores
Tavares, P; Marques, D; Malaca, P; Veiga, G; Costa, P; Moreira, AP;

Publicação
INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION

Abstract
Purpose In the vast majority of the individual robot installations, the robot arm is just one piece of a complex puzzle of components, such as grippers, jigs or external axis, that together compose an industrial robotic cell. The success of such installations is very dependent not only on the selection of such components but also on the layout and design of the final robotic cell, which are the main tasks of the system integrators. Consequently, successful robot installations are often empirical tasks owing to the high number of experimental combinations that could lead to exhaustive and time-consuming testing approaches. Design/methodology/approach A newly developed optimized technique to deal with automatic planning and design of robotic systems is proposed and tested in this paper. Findings The application of a genetic-based algorithm achieved optimal results in short time frames and improved the design of robotic work cells. Here, the authors show that a multi-layer optimization approach, which can be validated using a robotic tool, is able to help with the design of robotic systems. Originality/value To date, robotic solutions lack flexibility to cope with the demanding industrial environments. The results presented here formalize a new flexible and modular approach, which can provide optimal solutions throughout the different stages of design and execution control of any work cell.

2020

ROBIN: An open-source middleware for plug'n'produce of Cyber-Physical Systems

Autores
Arrais, R; Ribeiro, P; Domingos, H; Veiga, G;

Publicação
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS

Abstract
Motivated by the Fourth Industrial Revolution, there is an ever-increasing need to integrated Cyber-Physical Systems in industrial production environments. To address the demand for flexible robotics in contemporary industrial environments and the necessity to integrate robots and automation equipment in an efficient manner, an effective, bidirectional, reliable and structured data interchange mechanism is required. As an answer to these requirements, this article presents ROBIN, an open-source middleware for achieving interoperability between the Robot Operating System and CODESYS, a softPLC that can run on embedded devices and that supports a variety of fieldbuses and industrial network protocols. The referred middleware was successfully applied and tested in various industrial applications such as battery management systems, motion, robotic manipulator and safety hardware control, and horizontal integration between a mobile manipulator and a conveyor system.

2019

Testing the vertical and cyber-physical integration of cognitive robots in manufacturing

Autores
Krueger, V; Rovida, F; Grossmann, B; Petrick, R; Crosby, M; Charzoule, A; Garcia, GM; Behnke, S; Toscano, C; Veiga, G;

Publicação
Robotics and Computer-Integrated Manufacturing

Abstract

2019

Online inspection system based on machine learning techniques: real case study of fabric textures classification for the automotive industry

Autores
Malaca, P; Rocha, LF; Gomes, D; Silva, J; Veiga, G;

Publicação
Journal of Intelligent Manufacturing

Abstract
This paper focus on the classification, in real-time and under uncontrolled lighting, of fabric textures for the automotive industry. Many industrial processes have spatial constraints that limit the effective control of illumination of their vision based systems, hindering their effectiveness. The ability to overcome these problems using robust classification methods with suitable pre-processing techniques and choice of characteristics will increase the efficiency of this type of solutions with obvious production gains and thus economical. For this purpose, this paper studied and analyzed various pre-processing techniques, and selected the most appropriate fabric characteristics for the considered industrial case scenario. The methodology followed was based on the comparison of two different machine learning classifiers, ANN and SVM, using a large set of samples with a large variability of lightning conditions to faithfully simulate the industrial environment. The obtained solution shows the sensibility of ANN over SVM considering the number of features and the size of the training set, showing the better effectiveness and robustness of the last. The characteristics vector uses histogram equalization, Laws filter and Sobel filter, and multi-scale analysis. By using a correlation based method was possible to reduce the number of features used, achieving a better balanced between processing time and classification ratio. © 2016 Springer Science+Business Media New York

Teses
supervisionadas

2019

Development and Simulation of an Automatic Tool Changer for an ABB Robot

Autor
Paulo Jorge Leitão e Sousa

Instituição
UP-FEUP

2019

Towards “Industrie 4.0” in the context of investment casting industry

Autor
Isabel Maria Lousada Soares Figueiredo

Instituição
UP-FEUP

2019

Mobile Robotics Simulation for ROS Based Robots Using Visual Components

Autor
Gustavo Emanuel Barbosa Teixeira

Instituição
UP-FEUP

2019

Open Scalable Production System: An Industry 4.0 Framework for Cyber-Physical Systems

Autor
Rafael Lírio Arrais

Instituição
UP-FEUP

2018

Desenvolvimento de uma Aplicação para Geração Automática de Código para o PLC de Controlo de um Shuttle Car

Autor
Henrique Miguel Afonso Domingos

Instituição
UP-FEUP