ESTiG - Publicações em Proceedings Indexadas à WoS/Scopus
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Percorrer ESTiG - Publicações em Proceedings Indexadas à WoS/Scopus por Objetivos de Desenvolvimento Sustentável (ODS) "11:Cidades e Comunidades Sustentáveis"
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- A Comparison of PID Controller Architectures Applied in Autonomous UAV Follow up of UGVPublication . Bonzatto Junior, Luciano; Berger, Guido S.; Braun, João A.; Pinto, Milena F.; Santos, Murillo Ferreira dos; Oliveira Júnior, Alexandre de; Nowakowski, Marek; Costa, Paulo; Wehrmeister, Marco A.; Lima, JoséThe cooperation between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) has brought new perspectives and e!ectiveness to production and monitoring processes. In this sense, tracking moving targets in heterogeneous systems involves coordination, formation, and positioning systems between UGVs and UAVs. This article presents a Proportional-Integral-Derivative (PID) control strategy for tracking moving target operations, considering an operating environment between a multirotor UAV and an indoor UGV. Di!erent PID architectures are developed and compared to each other in the Gazebo simulator, whose objective is to analyze the control performance of the UAV when used to track the ground robot based on the identification of the ArUco fiducial marker. Computer vision techniques based on the Robot Operating System (ROS) are integrated into the UAV’s tracking system to provide a visual reference for the aircraft’s navigation system. The results of this study indicate that the PD, Cascade, and Parallel controllers showed similar performance in both trajectories tested, with the Parallel controller showing a slight advantage in terms of mean error and standard deviation, suggesting its suitability for applications that prioritize precision and stability.
- Artificial intelligence-based control of autonomous vehicles in simulation: a CNN vs. RL case studyPublication . Vasiljević, Ive; Musić, Josip; Lima, JoséThe article provides a comparison of Convolutional Neural Network (CNN) and Reinforcement Learning (RL) applied to the field of autonomous driving within the CARLA (CAr Learning to Act) simulator for training and evaluation. The analysis of results revealed CNNs better overall performance, as it demonstrated a more refined driving experience, shorter training durations, and a more straightforward learning curve and optimization process. However, it required data labelling. In contrast, RL relayed on an exhaustive (unsupervised) exploration of different models, ultimately selecting the model at timestep 600,000, which had the highest mean reward. Nevertheless, RL’s approach revealed its susceptibility to excessive oscillations and inconsistencies, necessitating additional optimization and tuning of hyperparameters and reward functions. This conclusion is further substantiated by a range of used performance metrics (objective and subjective), designed to assess the performance of each approach.
- Artificial intelligence-based user interaction module for autonomous mobile service robotsPublication . Alcantara, Carlos Boduar; Oliveira Júnior, Alexandre de; Costa, Julio; Ricken, Lucas; Mendes, Andre C.; Leitão, PauloWith the evolution of Artificial Intelligence (AI) technologies, there is a growing demand for Intelligent Personal Assistants (IPAs) that allow fluid communication with humans. However, there are still several challenges to overcome, such as difficulty in understanding nuances in some contexts. Therefore, this study seeks to mitigate these gaps by presenting a modular and scalable architecture for integrating IPAs into autonomous service robots. The architecture allows communication between various robot systems and peripherals with AI mechanisms, including Large Language Model (LLM) and Natural Language Processing, which seek to improve the user experience. The proposed architecture was applied to developing a service robot designed to guide and interact with people in a university environment, incorporating the RASA framework with an LLM for natural language processing and response generation. The paper discusses the adopted technologies, the current state of development, the difficulties encountered, and the analysis of the first feedback from volunteers.
- Digital innovation in tourism: exploring the potential of chatbotsPublication . Lopes, Isabel Maria; Guarda, Teresa; Oliveira, Pedro; Fernandes, Paula OdeteIn the last decade there has been a substantial increase in references to Artificial Intelligence (AI). AI has entered people’s lives, without them often realizing it. AI is increasingly present in our lives and in our daily lives, from our homes, transport, travel, industry, etc. It is inseparable to talk about AI without talking about chatbots. Therefore, the main objective of this study is to study the potential of chatbots in the tourism industry. For this purpose, a questionnaire was carried out among Higher Education students in Portugal, as it is understood that it is a good universe of study, since these technologies are still more associated with young audiences. On the other hand, also as a result of programs such as Erasmus, these young people travel more and are more aware of the potential of chatbots in tourism. The results of the questionnaire are presented in light of the literature and the responses collected, as well as the limitations of the present study. Future work that may mitigate the limitations of this research work are also presented.
- Human resources sptimization with multilayer perceptron: an automated selection toolPublication . Neto, Reginaldo G. de S.; Jatobá, Mariana N.; Santana, Matheus; Fernandes, Paula Sdete; Ferreira, João J.; Foleis, Juliano Henrique; Teixeira, João PauloThis study aims to create an artificial neural network (ANN) model with a multi-layer perceptron (MLP) architecture, designed to analyze the CVs of candidates for the position of sales consultant. To do this, a database of 600 CVs cataloged with scores from 0 to 10 by specialists with experience in recruitment and selection (R&S) is used. Fourteen characteristics are extracted from each CV, including ordinal and nominal attributes. A model with 3 hidden layers is used, which is trained with a split of 80% for training and 20% for testing. The activation function chosen for the hidden layers is the Rectified Linear Unit (ReLU), using the "adam" optimizer with a backpropagation algorithm during training using the Mean Squared Error (MSE) performance metric. The results show that the model is effective, giving a Mean Absolute Error (MAE) of 0.33, MSE of 0.37, Root Mean Squared Error (RMSE) of 0.61, and an r² Score of 0.96. These data not only confirm MLP's ability to replicate human accuracy but also suggest that such technologies can provide a faster and less biased tool for evaluating CVs. This performance of ANN indicates avenues for future research into the integration of other Artificial Intelligence (AI) technologies to refine the interpretation of less quantifiable characteristics, as well as making the process of R&S of new candidates in companies more agile.
- Hybrid wavefront and bidirectional A* coverage path planning for AGVs in photovoltaic farm inspectionPublication . Castro, Gabriel G.R.; Carvalho, Lucas L. M.; Marques, Diogo G.; Lima, José; Pinto, Milena F.This work presents a novel Coverage Path Planning (CPP) framework integrating theWavefront Algorithm with bidirectional A* to optimize path planning for Autonomous Ground Vehicles (AGVs) that inspect photovoltaic farms. The proposed framework combines the efficient propagation capabilities of the Wavefront Algorithm with the heuristic-driven optimization of bidirectional A*, comparing the results achieved to those from the individual algorithms. The framework was validated in a Software-In-The-Loop (SITL) simulation environment using Gazebo and the Robot Operating System (ROS), focusing on AGV-based inspection of ground infrastructure and cables beneath solar panels. The outcomes demonstrate significant coverage efficiency and overall robustness.
- Innovation and creativity in tourism, business and social sciencesPublication . Nunes, AlcinaThe accommodation and food services sector is vital to Portugal’s tourism industry, contributing significantly to economic output and employment. This study analyses the sector’s business dynamics from 2004 to 2022, focusing on key indicators such as business entry, exit, and survival rates. The research uses recent administrative data to examine in an exploratory manner how businesses within the sector have responded to significant economic challenges, including the global financial crisis and the COVID-19 pandemic. The findings reveal a resilient yet evolving sector, with a noticeable shift towards corporate consolidation and a decline in sole proprietorships. The study highlights the sector’s sensitivity to economic fluctuations, underscoring the need for strategic planning and policy intervention to support sustained growth and stability. These insights provide valuable guidance for policymakers and industry stakeholders seeking to navigate future economic uncertainties and foster a more robust accommodation and food services sector in Portugal.
- Nonlinear control of mecanum-wheeled robots applying h∞ controllerPublication . Chellal, Arezki Abderrahim; Braun, João A.; Lima, José; Gonçalves, José; Valente, António; Costa, PauloMecanum wheeled mobile robots have become relevant due to their excellent maneuverability, enabling omnidirectional motion in constrained environments as a requirement in industrial automation, logistics, and service robotics. This paper addresses a low-level controller based on the H-Infinity (H∞) control method for a four-wheel Mecanum mobile robot. The proposed controller ensures stability and performance despite model uncertainties and external disturbances. The dynamic model of the robot was developed and introduced in MATLAB to generate the controller. Further, the controller’s performance is validated and compared to a traditional PID controller using the SimTwo simulator, a realistic physics-based simulator with dynamics of rigid bodies incorporating non-linearities such as motor dynamics and friction effects. The preliminary simulation results show that the H∞ reached a time-independent Euclidean error of 0.0091 m, compared to 0.0154 m error for the PID in trajectory tracking. Demonstrating that the H∞ controller handles nonlinear dynamics and disturbances, ensuring precise trajectory tracking and improved system performance. This research validates the proposed approach for advanced control of Mecanum wheeled robots.
- Portable system and user interface for ECG and EMG acquisition, conditioning, and parameters extractionPublication . Luiz, Luiz E.; Silva, Wilson J. da; Soares, Salviano; Leitão, Paulo; Teixeira, João PauloElectrical signals from the human body are constantly the focus of research, searching for a better understanding of physiological events, discovering early signs of disease, and improving life quality. Developing devices that allow research beyond the usual requirements and allow easy adaptation regarding the system's acquisition, conditioning, and processing parts could be a step toward better understanding some behaviours. Therefore, this work focused on designing a system that goes from the discrete components to a graphical interface, allowing user control of parameters to set the acquisition in a way that favours the specific signal of interest. The resulting system allows the user to change parameters regarding the analogue and digital filtering, sampling frequency and events detection, namely R-peaks, in the electrocardiogram, to estimate heart rate and its frequency fluctuation, and muscle contraction in electromyogram, to analyse contraction strength and muscle fatigue. The system also allows the data to be stored, aiming to generate datasets to further process the data in AI-based algorithms.
- Smart carving of hard-shell fruit with CO2 laserPublication . Farrero, Bernardo; Babo, Pedro; Ribeiro, Luís Frölén; .The application of CO₂ laser technology in food processing has gained significant attention due to its precision and adaptability. This study presents an intelligent system for carving hard-shell fruits, specifically acorns, to facilitate their shelling process. The proposed approach integrates real-time control and monitoring technologies to enhance precision and efficiency. A key challenge in acorn processing is the size and shell thickness variability, which complicates mechanical carving. The developed system employs a CO₂ laser to create precise incisions, ensuring optimal shell cracking during dehydration while preventing kernel damage. Experimental tests conducted at the Polytechnic Institute of Bragança identified optimal parameters—6 seconds of laser exposure at 40𝑊 power—for consistent and controlled carving. A thoughtful analysis system was implemented to assess pre- and post-carving conditions, enabling real-time adjustments to laser settings. This self-optimizing process improves the efficiency of the shell carving while reducing waste. The results demonstrate the feasibility of automated acorn carving using CO₂ laser technology, offering a scalable solution for industrial food processing with continuous control of the shell incision. Future research could explore advanced automation techniques to enhance system robustness and adaptability to different fruit types.