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作者： A. Oliveira A. Dias T. Santos P. Rodrigues A. Martins E. Silva J. Almeida INESC TEC Institute for Systems and Computer Engineering Technology and Science Porto Portugal ISEP Instituto Superior de Engenharia do Porto Porto Portugal

Offshore wind farms are becoming the main alternative to fossil fuels and the future key to mitigating climate change by achieving energy sustainability. With favorable indicators in almost every environmental index, these structures operate under varying and dynamic environmental conditions, leading to efficiency losses and sudden failures. For these reasons, it’s fundamental to promote the development of autonomous solutions to monitor the health condition of the construction parts, preventing structural damage and accidents. This paper introduces a new simulation environment for testing and training autonomous inspection techniques under a more realistic offshore wind farm scenario. Combining the Gazebo simulator with ROS, this framework can include multi-robots with different sensors to operate in a customizable simulation environment regarding some external elements (fog, wind, buoyancy…). The paper also presents a use case composed of a 3D LiDAR-based technique for autonomous wind turbine inspection with UAV, including point cloud clustering, model estimation, and the preliminary results under this simulation framework using a mixed environment (offshore simulation with a real UAV platform).

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Industrial Digitalization Solutions for Precision Forestry Towards Forestry 4.0 1

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7th International Conference on Smart City Applications, SCA 2022

作者： Torres, Pedro M. B. Spencer, Geoffrey Neto, Luís Gonçalves, Gil Dionísio, Rogério Instituto Politécnico de Castelo Branco Castelo Branco6000-084 Portugal SYSTEC - Research Center for Systems and Technologies Porto4200-465 Portugal DiSAC - R &D Unit for Digital Services Applications and Content Castelo Branco6000-767 Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal

ISBN: (数字)9783031268526

ISBN: (纸本)9783031268519

This paper presents machine digitalization solutions with particular application in forest machines, such as harvesters and wood processing machines. In line with all the requirements of Industry 4.0, this type of machines also needs digitization to align with the concept defined as Forestry 4.0, where we think of a smarter forest in which all stakeholders, humans, forest producers, machines and factories communicate. For machine manufacturers is a step that must be taken to modernize machines, enabling remote access services for maintenance, productivity monitoring, and management of forest operations. It consists of developing cyber-physical systems around the machines with digital twins that allow the simulation and identification of faults that may occur. A solution is presented to enable CAN Bus communication between the controller, operator joysticks, and sensors/actuators, as well as a Digital Twin solution to emulate machine operations. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Industry 4.0

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Hybrid tourism recommendation system based on functionality/accessibility levels 15th

Hybrid tourism recommendation system based on functionality/...

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15th International Conference on Practical Applications of Agents and Multi-Agent systems, PAAMS 2017

作者： Santos, Filipe Almeida, Ana Martins, Constantino de Oliveira, Paulo Moura Gonçalves, Ramiro Computer Science Department Institute of Engineering Polytechnic of Porto Porto Portugal GECAD Knowledge and Decision Support Research Group Porto Portugal INESC TEC Trás-os-Montes e Alto Douro University Vila Real Portugal

ISBN: (纸本)9783319615776

This paper describes a proposal to develop a Tourism Recommendation System based in Users and Points-of-Interest (POI) functionality/accessibility levels. The focus is to evaluate if user’s physical and psychological functionality levels can perform an important role in recommendation results accuracy. This work also aims to show the importance of POI classification (accessibility levels are related with each POI ability to receive tourists with certain levels of physical and psychological issues), through the definition of a different model regarding their accessibility and other characteristics. © Springer International Publishing AG 2018.

关键词： Recommender systems

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Optimizing the fluidity in thin-section investment casting for vacuum induction molten AZ91D-1 %wt. CaO

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Journal of Magnesium and Alloys 2025年

作者： V.H. Carneiro V. Lopes I. Duarte H. Puga INESC TEC - Institute for Systems and Computer Engineering Technology and Science R. Dr. Roberto Frias 4200-465 Porto Portugal Department of Engineering School of Science and Technology - Universidade de Trás-os-Montes e Alto Douro Quinta de Prados 5001-801 Vila Real Portugal INL – International Iberian Nanotechnology Laboratory Avenida Mestre José Veiga 4715-330 Braga Portugal CMEMS-UMinho Department of Mechanical Engineering University of Minho Campus de Azurém 4800-058 Guimarães Portugal TEMA - Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Campus Universitário de Santiago 3810-193 Aveiro Portugal LASI - Intelligent Systems Associate Laboratory Campus Azurém 4800-058 Guimarães Portugal

This paper discusses an experimental investigation into the fluidity of AZ91D-1 %wt. CaO magnesium melt via induction for thin-section investment casting. Plaster molds with thin spiral cavities (0.5 to 1.5 mm square sections) were designed and manufactured to assess the impact of casting conditions on filling length, as magnesium alloys cause severe melting and melt-mold exothermic reactions, making investment casting challenging. Combinations of traditional Mg-mold reaction mitigation techniques, such as applying a protective mold coating (Yttria) and vacuum, were examined to determine their role in the filling process. The results suggest that when induction is employed to melt reactive alloys, these methods are not always beneficial, as initially thought. Particularly at higher melt temperatures, the combination of Yttria-coated molds with low-pressure vacuum induction significantly reduce fluidity: vacuum induced melt levitation which promotes oxidation with the residual atmosphere; and Yttria-coating cracking due to thermal stress during the mold fabrication slows filling and promotes significant melt-mold reaction. This study shows that best results to investment cast thin-sections are obtained by avoiding both vacuum and protective coatings, providing a viable route for the precision manufacturing of stent biomedical devices.

关键词： Az91d-1 %wt. cao Fluidity Investment casting Yttria-coating Vacuum

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Simulation environment for multi-robot cooperative 3D target perception

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8810卷 98-109页

作者： Dias, André Almeida, Jose Dias, Nuno Lima, Pedro Silva, Eduardo INESC TEC INESC Technology and Science ISEP/IPP School of Engineering Porto Portugal Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

Field experiments with a team of heterogeneous robots require human and hardware resources which cannot be implemented in a straightforward manner. Therefore, simulation environments are viewed by the robotic community as a powerful tool that can be used as an intermediate step to evaluate and validate the developments prior to their integration in real robots. This paper evaluates a novel multi-robot heterogeneous cooperative perception framework based on monocular measurements under the MORSE robotic simulation environment. The simulations are performed in an outdoor environment using a team of Micro Aerial Vehicles (MAV) and an Unmanned Ground Vehicle (UGV) performing distributed cooperative perception based on monocular measurements. The goal is to estimate the 3D target position. © Springer International Publishing Switzerland 2014.

关键词： Ground vehicles

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Street Light Segmentation in Satellite Images Using Deep Learning

Street Light Segmentation in Satellite Images Using Deep Lea...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ana Cláudia Teixeira Gabriel Carneiro Vitor Filipe António Cunha Joaquim J. Sousa University of Trás-os-Montes and Alto Douro Vila Real Portugal Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal

Public lighting plays a very important role for society's safety and quality of life. The identification of faults in public lighting is essential for the maintenance and prevention of safety. Traditionally, this task depends on human action, through checking during the day, representing expenditure and waste of energy. Automatic detection with deep learning is an innovative solution that can be explored for locating and identifying of this kind of problem. In this study, we present a first approach, composed of several steps, intending to obtain the segmentation of public lighting, using Seville (Spain) as case study. A dataset called NLight was created from a nighttime image taken by the JL1-3B satellite, and four U-Net and FPN architectures were trained with different backbones to segment part of the NLight. The U-Net with InceptionResNetv2 proved to be the model with the best performance, obtained 761 of 815, correct locations (93.4%). This model was used to predict the segmentation of the remaining dataset. This study provides the location of lamps so that we can identify patterns and possible lighting failures in the future.

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Wearable Glove Interaction with Robots

Wearable Glove Interaction with Robots

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2019 International Conference on engineering Applications, ICEA 2019

作者： Ferreira, N.M. Fonseca Silva, Marco Santos, Victor D.N. Santos, Frederico Miguel Santos, J. Candido B. Ferreira, Joao P. Institute for Systems and Computer Eng. Technology and Science-INESC TEC Rua Dr. Roberto Frias Porto4200-465 Portugal Coimbra Polytechnic ISEC Rua Pedro Nunes-Quinta da Nora Coimbra3030-199 Portugal Institute for Systems and Computers Engineering at Coimbra INESC Coimbra Rua Silvio Lima Polo II DEEC Coimbra3030-790 Portugal Telecommunications Institute Rua do Campo Alegre Porto4169-007 Portugal Institute of Systems and Robotics ISR DEEC Rua Sílvio Lima Pólo II Coimbra3030-290 Portugal

ISBN: (纸本)9781728129624

This paper presents the exciting use of robotics to teach technologies in an approach that motivates the students through intuitive learning. MSc degree programme students are engaged in strong team-building, while developing and testing new algorithms for mobile robotics and electronics areas. This project endows students with intuitive learning, and experimental results revealed that the integration of skills allows the students to develop applications for real scenarios. In this work it is described an application to control with hand gestures, several differential driven robots. © 2019 IEEE.

关键词： Students

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Contribution of PMSG based small wind generation systems to provide voltage control in low voltage networks

Contribution of PMSG based small wind generation systems to ...

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IEEE PES Innovative Smart Grid technologies Conference Europe (ISGT Europe)

作者： J. M. Rodrigues F. O. Resende C. L. Moreira Institute of Engineering and Computer Systems INESC-Porto Portugal University of Porto Porto Portugal

This paper proposes technical solutions that can be implemented in variable speed permanent magnet synchronous generators driven wind turbine systems aiming to mitigate high voltage problems in low voltage MicroGrids by controlling the active power output. Due to the limited control capability of these systems, controlling the output power to prevent voltage rise will require the local accommodation of the generation surplus. For this purpose, additional control functionalities are developed to be integrated in the control systems of the power electronic based interfaces. Their performance is evaluated through numerical simulations performed in Matlab ® /Simulink ® environment and considering the detailed models of the power electronic converters. The results obtained demonstrate the effectiveness of the proposed control functionalities.

关键词： Voltage control Control systems Wind turbines Rotors Wind power generation Batteries

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Automatic Identification of Public Lighting Failures in Satellite Images: A Case Study in Seville, Spain

Automatic Identification of Public Lighting Failures in Sate...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ana Cláudia Teixeira Leonor Batista Gabriel Carneiro António Cunha Joaquim J. Sousa University of Trás-os-Montes and Alto Douro Vila Real Portugal Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal

Public lighting is crucial for maintaining the safety and well-being of communities. Current inspection methods involve examining the luminaires during the day, but this approach has drawbacks, including energy consumption, delay in detecting issues, and high costs and time investment. Utilising deep learning based automatic detection is an advanced method that can be used for identifying and locating issues in this field. This study aims to use deep learning to automatically detect burnt-out street lights, using Seville (Spain) as a case study. The study uses high-resolution night time imagery from the JL1-3B satellite to create a dataset called NLight, which is then divided into three subsets: NL1, NL2, and NT. The NL1 and NL2 datasets are used to train and evaluate YOLOv5 and YOLOv7 segmentation models for instance segmentation of streets. And then, distance outliers were detected to find the lights off. Finally, the NT dataset is used to evaluate the effectiveness of the proposed methodology. The study finds that YOLOv5 achieved a mask mAP of 57.7%, and the proposed methodology had a precision of 30.8% and a recall of 28.3%. The main goal of this work is accomplished, but there is still space for future work to improve the methodology.

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Learning to Play Precision Ball Sports from scratch: a Deep Reinforcement Learning Approach

Learning to Play Precision Ball Sports from scratch: a Deep ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Liliana Antão Armando Sousa Luís Paulo Reis Gil Gonçalves SYSTEC - Research Center for Systems and Technologies FEUP - Faculty of Engineering University of Porto INESC TEC-INESC Technology and Science LIACC - Artificial Intelligence and Computer Science Laboratory

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Over the last years, robotics has increased its interest in learning human-like behaviors and activities. One of the most common actions searched, as well as one of the most fun to replicate, is the ability to play sports. This has been made possible with the steady increase of automated learning, encouraged by the tremendous developments in computational power and improved reinforcement learning (RL) *** paper implements a beginner Robot player for precision ball sports like boccia and bocce. A new simulated environment (PrecisionBall) is created, and a seven degree-of-freedom (DoF) robotic arm, is able to learn from scratch how to win the game and throw different types of balls towards the goal (the jack), using deep reinforcement learning. The environment is compliant with OpenAI Gym, using the MuJoCo realistic physics engine for a realistic simulation. A brief comparison of the convergence of different RL algorithms is performed. Several ball weights and various types of materials correspondent to bocce and boccia are tested, as well as different friction coefficients. Results show that the robot achieves a maximum success rate of 92.7% and mean of 75.7% for the best case. While learning to play these sports with the DDPG+HER algorithm, the robotic agent acquired some relevant skills that allowed it to win.

关键词： Machine learning Games Lifting equipment Task analysis Manipulators

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