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OCEANS

作者： Hugo Ferreira Alfredo Martins José Miguel Almeida António Valente António Figueiredo Batista da Cruz Maurício Camilo Victor Lobo Carlos Pinho Augustin Olivier Eduardo Silva ESEIG - School of Industrial Studies and Management Porto Polytechnic Institute INESC TEC - Institute for Systems Computer Engineering of Porto ISEP-School of Engineering Porto Polytechnic Institute PLY Technologies (Engineering) A Silva Matos Metalomecanica S.A CINAV (Portuguese Navy Research Center) INESC TEC - Institute for Systems and Computer Engineering of Porto

This paper describes the TURTLE project that aim to develop sub-systems with the capability of deep-sea long-term presence. Our motivation is to produce new robotic ascend and descend energy efficient technologies to be incorporated in robotic vehicles used by civil and military stakeholders for underwater operations. TURTLE contribute to the sustainable presence and operations in the sea bottom. Long term presence on sea bottom, increased awareness and operation capabilities in underwater sea and in particular on benthic deeps can only be achieved through the use of advanced technologies, leading to automation of operation, reducing operational costs and increasing efficiency of human activity.

关键词： Vehicles Oceans Robots Underwater vehicles Observatories Shape Instruments

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Explanatory and Causal Analysis of the MIBEL Electricity Market Spot Price

Explanatory and Causal Analysis of the MIBEL Electricity Mar...

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Power tech Conference

作者： Carla Gonçalves Miguel Ribeiro João Viana Renato Fernandes José Villar Ricardo Bessa Gonçalo Correia José Sousa Virgílio Mendes Ana Cristina Nunes INESC TEC-Institute for Systems and Computer Engineering Technology and Science Porto Portugal EDP Produção Porto Portugal

This paper analyzes the electricity prices of the MIBEL electricity spot market with respect to a set of possible explanatory variables. Understanding the main drivers of the electricity price is a key aspect in understanding price formation and in developing forecasting models, which are essential for the selling and buying strategies of market agents. For this analysis, different techniques have been applied in this work, including standard and lasso regression models, causal analysis based on bayesian networks and classification trees. Results from the different approaches are coherent and show strong dependency of the electricity prices with the Portuguese imported coal for lower non-dispatchable net demands, which has been progressively replaced by gas for larger non-dispatchable net demands. Hydro reservoirs and hydro production are also main explanatory variables of the electricity price for all non-dispatchable net demand levels.

关键词： Indexes Regression tree analysis Classification tree analysis

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Line Fitting-Based Corner-Like Detector for 2D Laser Scanners Data∗ 10

Line Fitting-Based Corner-Like Detector for 2D Laser Scanner...

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10th International Conference on Automation, Robotics, and Applications, ICARA 2024

作者： Sousa, Ricardo B. Sobreira, Heber Miguel Silva, Manuel F. Moreira, Antonio Paulo University of Porto Faculty of Engineering Porto4200-465 Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal ISEP Polytechnic of Porto R. Dr. António Bernardinode Almeida Porto4249-015 Portugal

ISBN: (纸本)9798350394245

The extraction of geometric information from the environment may be of interest to localisation and mapping algorithms. Existent literature on extracting geometric features from 2D laser data focuses mainly on detecting lines. Regarding corners, most methodologies use the intersection of line segment features. This paper presents a feature extraction algorithm for corner-like points in the 2D laser scan. The proposed methodol-ogy defines arrival and departure neighbourhoods around each scan point and performs local line fitting evaluated in multiple distance-based scales. Then, a set of indicators based on line fitting error, the angle between arrival and departure lines, and consecutive observation of the same keypoint across different scales determine the existence of a corner-like feature. The experiments evaluated the corner-like features regarding their relative position and observability, achieving standard deviations on the relative position lower than the sensor noise and visibility ratios higher than 75% with very low false positives rates. © 2024 IEEE.

关键词： Feature extraction

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Performing Aerobatic Maneuver with Imitation Learning 23rd

Performing Aerobatic Maneuver with Imitation Learning

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23rd International Conference on Computational Science, ICCS 2023

作者： Freitas, Henrique Camacho, Rui Silva, Daniel Castro Department of Informatics Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias s/n. Porto4200-465 Portugal LIAAD/INESC TEC - Artificial Intelligence and Decision Support Laboratory/Institute for Systems and Computer Engineering Technology and Science Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal

ISBN: (纸本)9783031359941

The work reported in this article addresses the challenge of building models for non-trivial aerobatic aircraft maneuvers in an automated fashion. It is built using a Behavioural Cloning approach where human pilots provide a set of example maneuvers used by a Machine Learning algorithm to induce a control model for each maneuver. The best examples for each maneuver were selected using a set of objective evaluation metrics. Using those example sets, robust models were induced that could replicate (and in some cases outperform) the human pilots that provided the examples (the clean-up effect). Complete complex maneuvers were performed using a meta-controller capable of sequencing the basic ones learned by imitation. This endeavor was rewarded by the results that show several Machine Learning models capable of performing highly complex aircraft maneuvers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloning

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Next-generation smart homes: CO 2 monitoring with Matter protocol to support indoor air quality

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Internet of Things 2025年

作者： Afonso Mota Carlos Serôdio Ana Briga-Sá Antonio Valente Department of Engineering School of Sciences and Technology Universidade de Trás-os-Montes e Alto Douro (UTAD) 5000-801 Vila Real Portugal Center ALGORITMI Universidade do Minho Campus de Azurém Guimarães 4800-058 Portugal CQ-VR (Center of Chemistry of Vila Real) Universidade de Trás-os-Montes e Alto Douro 5000-801 Vila Real Portugal CRIIS (Centre for Robotics in Industry and Intelligent Systems) INESC-TEC—Institute for Systems and Computer Engineering Technology and Science Campus da FEUP Porto 4200-465 Portugal

Humans spend most of their time indoors, where air quality and comfort are crucial to health and well-being. Elevated CO 2 levels in buildings can reduce cognitive function, discomfort, and health issues. Indoor CO 2 monitoring has emerged as a key focus in the literature, particularly in residential buildings, as it can play a vital role in helping to maintain adequate ventilation rates. The growing smart home market demands seamless integration and control, which are essential for implementing IAQ sensing devices. However, interoperability barriers between platforms and devices continue to hinder smart home adoption. To address these challenges, Matter protocol is starting to appear in the market. In this work, a wireless CO 2 sensor is developed based on ESP32-C6 and SCD40 and integrated into a created Matter-enabled ecosystem formed with the Home Assistant open-source platform. The utilized hardware and software enable the usage of two different wireless communication technologies, WiFi and Thread, enhancing compatibility. The study highlights the rapid and seamless onboarding of the developed CO 2 monitoring device into smart home ecosystems using the Matter protocol. As a result, once the device is successfully added to the ecosystem, the measurements can be accessed and analyzed through a mobile application, forming an IoT environment.

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Explanatory and Causal Analysis of the Portuguese Manual Balancing Reserve

Explanatory and Causal Analysis of the Portuguese Manual Bal...

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Power tech Conference

作者： Carla Gonçalves Miguel Ribeiro João Viana Renato Fernandes José Villar Ricardo Bessa Gonçalo Correia José Sousa Virgílio Mendes Ana Cristina Nunes INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal EDP Produção Porto Portugal

This paper analyzes the activation of the manual balancing reserve of the Portuguese system and its prices for the period 2015-2017. Standard, logistic and LASSO regression models, causal analysis based on Bayesian networks and random forests are applied. Results show that the variables that better explain the activation of the manual reserve are the imbalances of both renewable generation and demand, but surprisingly forecasted with persistence models based on the last verified measurements (available 15 minutes before the reserve activation), instead of using more elaborated models based on production forecasts. Prices, however, are harder to explain suggesting the need for additional information, such as bidding prices not used in this study.

关键词： Analytical models Schedules Manuals Production Predictive models Real-time systems Time measurement

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Low Cost Underwater Acoustic Positioning System with a Simplified DoA Algorithm

Low Cost Underwater Acoustic Positioning System with a Simpl...

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OCEANS

作者： Pedro Guedes Nuno Viana José Silva Guilherme Amaral Hugo Ferreira André Dias José Miguel Almeida Alfredo Martins Eduardo Silva ISEP School of Engineering Polythecnhic Institute of Porto Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

For the context of a mobile tracking system, an underwater acoustic positioning system was developed, using three hydrophones to compute the direction of an acoustic source relative to an Autonomous Surface Vehicle (ASV). The paper presents an algorithm for the Direction of Arrival (DoA) of an acoustic source, which allows to estimate its position. Preliminary results will be shown in this paper relative to the detection and identification (ID) of the acoustic sources, as well as an analysis of the proposed algorithm. The solution allows the position estimation of an acoustic source, which can be used in tracking solutions. The system can be applied in an ASV or fixed buoys, as long as the baseline's hydrophones are at equal angular distances. The main objective is to track targets with the DoA algorithm as well to estimate their position, improving what was done in [1].

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A Comparison between NSGA-II and NSGA-III to Solve Multi-Objective Sectorization Problems based on Statistical Parameter Tuning

A Comparison between NSGA-II and NSGA-III to Solve Multi-Obj...

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Circuits, systems, Communications and computers (CSCC), International Conference on

作者： Aydin Teymourifar Ana Maria Rodrigues José Soeiro Ferreira INESC TEC - Institute for Systems and Computer Engineering Porto Portugal INESC TEC and CEOS.PP - Centre for Organisational and Social Studies of P.Porto Polytechnic of Porto Porto Portugal Faculty of Engineering INESC TEC and FEUP University of Porto Porto Portugal

This paper compares the non-dominated sorting genetic algorithm (NSGA-II) and NSGA-III to solve multiobjective sectorization problems (MO-SPs). We focus on the effects of the parameters of the algorithms on their performance and we use statistical experimental design to find more effective parameters. For this purpose, the analysis of variance (ANOVA), Taguchi design and response surface method (RSM) are used. The criterion of the comparison is the number of obtained nondominated solutions by the algorithms. The aim of the problem is to divide a region that contains distribution centres (DCs) and customers into smaller and balanced regions in terms of demands and distances, for which we generate benchmarks. The results show that the performance of algorithms improves with appropriate parameter definition. With the parameters defined based on the experiments, NSGA-III outperforms NSGA-II.

关键词： computers Benchmark testing Response surface methodology Analysis of variance Tuning Sorting Genetic algorithms

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Robot 2015: Second Iberian Robotics conference: Advances in robotics, volume 1 2nd

Robot 2015: Second Iberian Robotics conference: Advances in ...

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2nd Iberian Robotics Conference, ROBOT 2015

作者： Reis, Luís Paulo Moreira, António Paulo Lima, Pedro U. Montano, Luis Muñoz-Martinez, Victor University of Minho School of Engineering Information Systems Department Guimarães Portugal University of Porto INESC-TEC Porto Portugal University of Lisbon Instituto Superior Técnico Institute for Systems and Robotics Lisboa Portugal University of Zaragoza School of Engineering and Architecture Computer Systems Engineering Department Zaragoza Spain University of Malaga Superior Technical School of Industrial Engineers Automatic Control Systems Engineering Department Málaga Spain

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A Multimodal Learning-based Approach for Autonomous Landing of UAV

A Multimodal Learning-based Approach for Autonomous Landing ...

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IEEE/ASME International Conference on Mechtronic and Embedded systems and Applications, MESA

作者： Francisco S. Neves Luís M. Branco Maria I. Pereira Rafael M. Claro Andry M. Pinto Department of Electrical and Computer Engineering (DEEC) Faculty of Engineering of University of Porto (FEUP) Institute for Systems and Computer Engineering - Technology and Science (INESC TEC) Porto Portugal

ISBN: (数字)9798331516239

ISBN: (纸本)9798331516246

In the field of autonomous Unmanned Aerial Vehicles (UAVs) landing, conventional approaches fall short in delivering not only the required precision but also the resilience against environmental disturbances. Yet, learning-based algorithms can offer promising solutions by leveraging their ability to learn the intelligent behaviour from data. On one hand, this paper introduces a novel multimodal transformer-based Deep Learning detector, that can provide reliable positioning for precise autonomous landing. It surpasses standard approaches by addressing individual sensor limitations, achieving high reliability even in diverse weather and sensor failure conditions. It was rigorously validated across varying environments, achieving optimal true positive rates and average precisions of up to 90%. On the other hand, it is proposed a Reinforcement Learning (RL) decision-making model, based on a Deep Q-Network (DQN) rationale. Initially trained in simulation, its adaptive behaviour is successfully transferred and validated in a real outdoor scenario. Furthermore, this approach demonstrates rapid inference times of approximately 5ms, validating its applicability on edge devices.

关键词： Training Wind Image edge detection Decision making Detectors Reinforcement learning Robot sensing systems Autonomous aerial vehicles Transformers Resilience

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