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This service develops advanced solutions in automation and industrial robotics, including handlers and mobile robots, and promotes the integration of control intelligent systems and sensing.

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Browsing CRIIS by Author "5364"
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    A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario
    ( 2021) Santos,J ; Paulo Miranda Rebelo ; Luís Freitas Rocha ; Pedro Gomes Costa ; Germano Veiga ; 5159 ; 5364 ; 5674 ; 7077
    A multi-AGV based logistic system is typically associated with two fundamental problems, critical for its overall performance: the AGV’s route planning for collision and deadlock avoidance; and the task scheduling to determine which vehicle should transport which load. Several heuristic functions can be used according to the application. This paper proposes a time-based algorithm to dynamically control a fleet of Autonomous Guided Vehicles (AGVs) in an automatic warehouse scenario. Our approach includes a routing algorithm based on the A* heuristic search (TEA*—Time Enhanced A*) to generate free-collisions paths and a scheduling module to improve the results of the routing algorithm. These modules work cooperatively to provide an efficient task execution time considering as basis the routing algorithm information. Simulation experiments are presented using a typical industrial layout for 10 and 20 AGVs. Moreover, a comparison with an alternative approach from the state-of-the-art is also presented.
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    AdaptPack studio translator: translating offline programming to real palletizing robots
    ( 2020) Silva,MF ; João Pedro Souza ; Castro,AL ; Luís Freitas Rocha ; 5364 ; 7366
    Purpose This paper aims to propose a translation library capable of generating robots proprietary code after their offline programming has been performed in a software application, named AdaptPack Studio, running over a robot simulation and offline programming software package. Design/methodology/approach The translation library, named AdaptPack Studio Translator, is capable to generate proprietary code for the Asea Brown Boveri, FANUC, Keller und Knappich Augsburg and Yaskawa Motoman robot brands, after their offline programming has been performed in the AdaptPack Studio application. Findings Simulation and real tests were performed showing an improvement in the creation, operation, modularity and flexibility of new robotic palletizing systems. In particular, it was verified that the time needed to perform these tasks significantly decreased. Practical implications The design and setup of robotics palletizing systems are facilitated by an intuitive offline programming system and by a simple export command to the real robot, independent of its brand. In this way, industrial solutions can be developed faster, in this way, making companies more competitive. Originality/value The effort to build a robotic palletizing system is reduced by an intuitive offline programming system (AdaptPack Studio) and the capability to export command to the real robot using the AdaptPack Studio Translator. As a result, companies have an increase in competitiveness with a fast design framework. Furthermore, and to the best of the author’s knowledge, there is also no scientific publication formalizing and describing how to build the translators for industrial robot simulation and offline programming software packages, being this a pioneer publication in this area.
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    AdaptPack Studio: an automated intelligent framework for offline factory programming
    ( 2020) João Pedro Souza ; Manuel Santos Silva ; Luís Freitas Rocha ; Castro,AL ; 5655 ; 7366 ; 5364
    Purpose This paper aims to propose an automated framework for agile development and simulation of robotic palletizing cells. An automatic offline programming tool, for a variety of robot brands, is also introduced. Design/methodology/approach This framework, named AdaptPack Studio, offers a custom-built library to assemble virtual models of palletizing cells, quick connect these models by drag and drop, and perform offline programming of robots and factory equipment in short steps. Findings Simulation and real tests performed showed an improvement in the design, development and operation of robotic palletizing systems. The AdaptPack Studio software was tested and evaluated in a pure simulation case and in a real-world scenario. Results have shown to be concise and accurate, with minor model displacement inaccuracies because of differences between the virtual and real models. Research limitations/implications An intuitive drag and drop layout modeling accelerates the design and setup of robotic palletizing cells and automatic offline generation of robot programs. Furthermore, A* based algorithms generate collision-free trajectories, discretized both in the robot joints space and in the Cartesian space. As a consequence, industrial solutions are available for production in record time, increasing the competitiveness of companies using this tool. Originality/value The AdaptPack Studio framework includes, on a single package, the possibility to program, simulate and generate the robot code for four different brands of robots. Furthermore, the application is tailored for palletizing applications and specifically includes the components (Building Blocks) of a particular company, which allows a very fast development of new solutions. Furthermore, with the inclusion of the Trajectory Planner, it is possible to automatically develop robot trajectories without collisions.
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    AdaptPack Studio: Automatic Offline Robot Programming Framework for Factory Environments
    ( 2019) João Pedro Souza ; Manuel Santos Silva ; Luís Freitas Rocha ; Castro,A ; 5655 ; 7366 ; 5364
    The brisk and dynamic environment that factories are facing, both as an internal and an external level, requires a collection of handy tools to solve emerging issues in the industry 4.0 context. Part of the common challenges that appear are related to the increasing demand for high adaptability in the organizations' production lines. Mechanical processes are becoming faster and more adjustable to the production diversity in the Fast Moving Consumer Goods (FMCG). Concerning the previous characteristics, future factories can only remain competitive and profitable if they have the ability to quickly adapt all their production resources in response to inconstant market demands. Having previous concerns in focus, this paper presents a fast and adaptative framework for automated cells modeling, simulation and offline robot programming, focused on palletizing operations. Established as an add-on for the Visual Components (VC) 3D manufacturing simulation software, the proposed application allows performing fast layout modeling and automatic offline generation of robot programs. Furthermore, A* based algorithms are used for generating collision-free trajectories, discretized both in the robot joints space and in the Cartesian space. The software evaluation was tested inside the VC simulation world and in the real-world scenario. Results have shown to be concise and accurate, with minor displacement inaccuracies due to differences between the virtual model and the real world. © 2019 IEEE.
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    Automatic generation of disassembly sequences and exploded views from solidworks symbolic geometric relationships
    ( 2018) Carlos Miguel Costa ; Thomas,U ; Cardoso,HL ; Oliveira,EC ; Luís Freitas Rocha ; Armando Sousa ; Germano Veiga ; 6164 ; 5152 ; 5364 ; 5674
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    Autonomous Robot Navigation for Automotive Assembly Task: An Industry Use-Case
    ( 2019) Héber Miguel Sobreira ; Germano Veiga ; António Paulo Moreira ; Rodrigues,F ; Lima,J ; Luís Freitas Rocha ; 5364 ; 5424 ; 5674 ; 5157
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    Bin Picking Approaches Based on Deep Learning Techniques: A State-of-the-Art Survey
    ( 2022) Cordeiro,A ; Luís Freitas Rocha ; Carlos Miguel Costa ; Pedro Gomes Costa ; Manuel Santos Silva ; 5159 ; 5364 ; 5655 ; 6164
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    Collaborative Welding System using BIM for Robotic Reprogramming and Spatial Augmented Reality
    ( 2019) Carlos Miguel Costa ; Luís Freitas Rocha ; Malaca,P ; Pedro Gomes Costa ; António Paulo Moreira ; Tavares,P ; Armando Sousa ; Germano Veiga ; 6164 ; 5152 ; 5157 ; 5159 ; 5364 ; 5674
    The optimization of the information flow from the initial design and through the several production stages plays a critical role in ensuring product quality while also reducing the manufacturing costs. As such, in this article we present a cooperative welding cell for structural steel fabrication that is capable of leveraging the Building Information Modeling (BIM) standards to automatically orchestrate the necessary tasks to be allocated to a human operator and a welding robot moving on a linear track. We propose a spatial augmented reality system that projects alignment information into the environment for helping the operator tack weld the beam attachments that will be later on seam welded by the industrial robot. This way we ensure maximum flexibility during the beam assembly stage while also improving the overall productivity and product quality since the operator no longer needs to rely on error prone measurement procedures and he receives his tasks through an immersive interface, relieving him from the burden of analyzing complex manufacturing design specifications. Moreover, no expert robotics knowledge is required to operate our welding cell because all the necessary information is extracted from the Industry Foundation Classes (IFC), namely the CAD models and welding sections, allowing our 3D beam perception systems to correct placement errors or beam bending, which coupled with our motion planning and welding pose optimization system ensures that the robot performs its tasks without collisions and as efficiently as possible while maximizing the welding quality. © 2019 Elsevier B.V.
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    Comparison of 3D Sensors for Automating Bolt-Tightening Operations in the Automotive Industry
    ( 2023) Dias,J ; Simões,P ; Soares,N ; Costa,CM ; Petry,MR ; Veiga,G ; Luís Freitas Rocha ; 5364
    Machine vision systems are widely used in assembly lines for providing sensing abilities to robots to allow them to handle dynamic environments. This paper presents a comparison of 3D sensors for evaluating which one is best suited for usage in a machine vision system for robotic fastening operations within an automotive assembly line. The perception system is necessary for taking into account the position uncertainty that arises from the vehicles being transported in an aerial conveyor. Three sensors with different working principles were compared, namely laser triangulation (SICK TriSpector1030), structured light with sequential stripe patterns (Photoneo PhoXi S) and structured light with infrared speckle pattern (Asus Xtion Pro Live). The accuracy of the sensors was measured by computing the root mean square error (RMSE) of the point cloud registrations between their scans and two types of reference point clouds, namely, CAD files and 3D sensor scans. Overall, the RMSE was lower when using sensor scans, with the SICK TriSpector1030 achieving the best results (0.25 mm ± 0.03 mm), the Photoneo PhoXi S having the intermediate performance (0.49 mm ± 0.14 mm) and the Asus Xtion Pro Live obtaining the higher RMSE (1.01 mm ± 0.11 mm). Considering the use case requirements, the final machine vision system relied on the SICK TriSpector1030 sensor and was integrated with a collaborative robot, which was successfully deployed in an vehicle assembly line, achieving 94% success in 53,400 screwing operations.
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    Converting Robot Offline Programs to Native Code Using the AdaptPack Studio Translators
    ( 2019) João Pedro Souza ; Manuel Santos Silva ; Relvas,P ; Luís Freitas Rocha ; Castro,A ; 5655 ; 7366 ; 5364
    The increase in productivity is a demand for modern industries that need to be competitive in the actual business scenario. To face these challenges, companies are increasingly using robotic systems for end-of-line production tasks, such as wrapping and palletizing, as a mean to enhance the production line efficiency and products traceability, allowing human operators to be moved to more added value operations. Despite this increasing use of robotic systems, these equipments still present some inconveniences regarding the programming procedure, as the time required for its execution does not meet the current industrial needs. To face this drawback, offline robot programming methods are gaining great visibility, as their flexibility and programming speed allows companies to face the need of successive changes in the production line set-up. However, even with a great number of robots and simulators that are available in market, the efforts to support several robot brands in one software did not reach the needs of engineers. Therefore, this paper proposes a translation library named AdaptPack Studio Translator, which is capable to export proprietary codes for the ABB, Fanuc, Kuka, and Yaskawa robot brands, after their offline programming has been performed in the Visual Components software. The results presented in this paper are evaluated in simulated and real scenarios. © 2019 IEEE.
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    Enhanced Performance Real-Time Industrial Robot Programming by Demonstration using Stereoscopic Vision and an IMU sensor
    ( 2020) Amorim,A ; Vitor Hugo Pinto ; Luís Freitas Rocha ; Moreira,AP ; 6852 ; 5364
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    Force control heuristics for surpassing pose uncertainty in mobile robotic assembly platforms
    ( 2021) Duarte Alão Magalhães ; Paulo Miranda Rebelo ; Carlos Miguel Costa ; Luís Freitas Rocha ; Germano Veiga ; 5364 ; 5674 ; 7077 ; 8275 ; 6164
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    Map-Matching Algorithms for Robot Self-Localization: A Comparison Between Perfect Match, Iterative Closest Point and Normal Distributions Transform
    ( 2019) Héber Miguel Sobreira ; António Paulo Moreira ; Paulo José Costa ; Farias,PCMA ; José Lima ; Luís Freitas Rocha ; Sousa,I ; Carlos Miguel Costa ; 6164 ; 5153 ; 5156 ; 5157 ; 5364 ; 5424
    The self-localization of mobile robots in the environment is one of the most fundamental problems in the robotics navigation field. It is a complex and challenging problem due to the high requirements of autonomous mobile vehicles, particularly with regard to the algorithms accuracy, robustness and computational efficiency. In this paper, we present a comparison of three of the most used map-matching algorithms applied in localization based on natural landmarks: our implementation of the Perfect Match (PM) and the Point Cloud Library (PCL) implementation of the Iterative Closest Point (ICP) and the Normal Distribution Transform (NDT). For the purpose of this comparison we have considered a set of representative metrics, such as pose estimation accuracy, computational efficiency, convergence speed, maximum admissible initialization error and robustness to the presence of outliers in the robots sensors data. The test results were retrieved using our ROS natural landmark public dataset, containing several tests with simulated and real sensor data. The performance and robustness of the Perfect Match is highlighted throughout this article and is of paramount importance for real-time embedded systems with limited computing power that require accurate pose estimation and fast reaction times for high speed navigation. Moreover, we added to PCL a new algorithm for performing correspondence estimation using lookup tables that was inspired by the PM approach to solve this problem. This new method for computing the closest map point to a given sensor reading proved to be 40 to 60 times faster than the existing k-d tree approach in PCL and allowed the Iterative Closest Point algorithm to perform point cloud registration 5 to 9 times faster. © 2018 Springer Science+Business Media B.V., part of Springer Nature
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    Modeling of video projectors in OpenGL for implementing a spatial augmented reality teaching system for assembly operations
    ( 2019) Rui Pedro Rodrigues ; Thomas,U ; Carlos Miguel Costa ; Germano Veiga ; Armando Sousa ; Luís Freitas Rocha ; Augusto Sousa ; 5674 ; 5364 ; 5152 ; 5579 ; 197 ; 6164
    Teaching complex assembly and maintenance skills to human operators usually requires extensive reading and the help of tutors. In order to reduce the training period and avoid the need for human supervision, an immersive teaching system using spatial augmented reality was developed for guiding inexperienced operators. The system provides textual and video instructions for each task while also allowing the operator to navigate between the teaching steps and control the video playback using a bare hands natural interaction interface that is projected into the workspace. Moreover, for helping the operator during the final validation and inspection phase, the system projects the expected 3D outline of the final product. The proposed teaching system was tested with the assembly of a starter motor and proved to be more intuitive than reading the traditional user manuals. This proof of concept use case served to validate the fundamental technologies and approaches that were proposed to achieve an intuitive and accurate augmented reality teaching application. Among the main challenges were the proper modeling and calibration of the sensing and projection hardware along with the 6 DoF pose estimation of objects for achieving precise overlap between the 3D rendered content and the physical world. On the other hand, the conceptualization of the information flow and how it can be conveyed on-demand to the operator was also of critical importance for ensuring a smooth and intuitive experience for the operator. © 2019 IEEE.
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    Modeling of video projectors in OpenGL for implementing a spatial augmented reality teaching system for assembly operations
    ( 2019) Germano Veiga ; Carlos Miguel Costa ; Rui Pedro Rodrigues ; Augusto Sousa ; Luís Freitas Rocha ; Thomas,U ; Armando Sousa ; 197 ; 5579 ; 5152 ; 5364 ; 5674 ; 6164
    Teaching complex assembly and maintenance skills to human operators usually requires extensive reading and the help of tutors. In order to reduce the training period and avoid the need for human supervision, an immersive teaching system using spatial augmented reality was developed for guiding inexperienced operators. The system provides textual and video instructions for each task while also allowing the operator to navigate between the teaching steps and control the video playback using a bare hands natural interaction interface that is projected into the workspace. Moreover, for helping the operator during the final validation and inspection phase, the system projects the expected 3D outline of the final product. The proposed teaching system was tested with the assembly of a starter motor and proved to be more intuitive than reading the traditional user manuals. This proof of concept use case served to validate the fundamental technologies and approaches that were proposed to achieve an intuitive and accurate augmented reality teaching application. Among the main challenges were the proper modeling and calibration of the sensing and projection hardware along with the 6 DoF pose estimation of objects for achieving precise overlap between the 3D rendered content and the physical world. On the other hand, the conceptualization of the information flow and how it can be conveyed on-demand to the operator was also of critical importance for ensuring a smooth and intuitive experience for the operator.
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    On the development of a collaborative robotic system for industrial coating cells
    ( 2021) Rafael Lírio Arrais ; Carlos Miguel Costa ; Ribeiro,P ; Luís Freitas Rocha ; Manuel Santos Silva ; Germano Veiga ; 5364 ; 6164 ; 6551 ; 5655 ; 5674
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    Online inspection system based on machine learning techniques: real case study of fabric textures classification for the automotive industry
    ( 2019) Luís Freitas Rocha ; Malaca,P ; Germano Veiga ; Silva,J ; Gomes,D ; 5364 ; 5674
    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
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    An overview of pruning and harvesting manipulators
    ( 2022) Vítor Tinoco ; Manuel Santos Silva ; Filipe Neves Santos ; António Valente ; Luís Freitas Rocha ; Sandro Augusto Magalhães ; Luís Carlos Santos ; 5364 ; 5655 ; 5762 ; 7150 ; 7481 ; 8387 ; 5552
    Purpose The motivation for robotics research in the agricultural field has sparked in consequence of the increasing world population and decreasing agricultural labor availability. This paper aims to analyze the state of the art of pruning and harvesting manipulators used in agriculture. Design/methodology/approach A research was performed on papers that corresponded to specific keywords. Ten papers were selected based on a set of attributes that made them adequate for review. Findings The pruning manipulators were used in two different scenarios: grapevines and apple trees. These manipulators showed that a light-controlled environment could reduce visual errors and that prismatic joints on the manipulator are advantageous to obtain a higher reach. The harvesting manipulators were used for three types of fruits: strawberries, tomatoes and apples. These manipulators revealed that different kinematic configurations are required for different kinds of end-effectors, as some of these tools only require movement in the horizontal axis and others are required to reach the target with a broad range of orientations. Originality/value This work serves to reduce the gap in the literature regarding agricultural manipulators and will support new developments of novel solutions related to agricultural robotic grasping and manipulation.
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    Path Planning Algorithms Benchmarking for Grapevines Pruning and Monitoring
    ( 2019) Sandro Augusto Magalhães ; Filipe Neves Santos ; Rui Costa Martins ; Luís Freitas Rocha ; Brito,J ; 5552 ; 5364 ; 7481 ; 6905
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    Quality Control of Casting Aluminum Parts: A Comparison of Deep Learning Models for Filings Detection
    ( 2023) Luís Freitas Rocha ; Manuel Santos Silva ; Cláudia Daniela Rocha ; Rui Pedro Nascimento ; 5364 ; 5655 ; 6709 ; 9050