PG-EAM - Graduate Program in Aeronautical and Mechanical Engineering
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Emilia Villani

Emilia Villani

13
h-index
632
Citations
92
Articles

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Last Update: 2026-06-25

Publications (92)

92 publications
Article 2025

Eye-tracking analysis to assess the mental load of unmanned aerial system operators: systematic review and future directions

Russo, A. C. , Cardoso, M. M. , Villani, E.

Aeronautical Journal , vol. 129 (1333) , pp. 529-558
Citations: 2
Show abstract

© The Author(s), 2024.This article presents a systematic review on the use of eye-tracking technology to assess the mental workload of unmanned aircraft system (UAS) operators. With the increasing use of unmanned aircraft in military and civilian operations, understanding the mental workload of these operators has become essential for ensuring mission effectiveness and safety. The review covered 26 studies that explored the application of eye-tracking to capture nuances of visual attention and assess cognitive load in real-time. Traditional methods such as self-assessment questionnaires, although useful, showed limitations in terms of accuracy and objectivity, highlighting the need for advanced approaches like eye-tracking. By analysing gaze patterns in simulated environments that reproduce real challenges, it was possible to identify moments of higher mental workload, areas of concentration and sources of distraction. The review also discussed strategies for managing mental workload, including adaptive design of human-machine interfaces. The analysis of the studies revealed a growing relevance and acceptance of eye-tracking as a diagnostic and analytical tool, offering guidelines for the development of interfaces and training that dynamically respond to the cognitive needs of operators. It was concluded that eye-tracking technology can significantly contribute to the optimisation of UAS operations, enhancing both the safety and efficiency of military and civilian missions.

Article 2025

Virtual Reality for the Human-Centred Design of Assistive Devices

de Souza Rehder, Ivan , Junior, Moacyr Cardoso Machado , da Silva, Edmar Thomaz , Villani, Emilia

Springer Series in Design and Innovation , vol. 56 , pp. 480-485
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© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.The development of assistive devices for the blind and visually impaired (BVI) has often overlooked the essential participation of BVI users in the design process, resulting in products that are not user-friendly for them. This paper introduces a virtual reality (VR)-based framework designed to integrate BVI users into the development of assistive technologies actively. Leveraging VR, the framework facilitates immersive and interactive product testing environments where BVI users can directly evaluate and provide feedback on assistive device prototypes. This method allows for real time adjustments and refinements, significantly enhancing the usability of the products. The setup integrates two scenarios, one virtual and one real, each built with identical configurations. As BVI users navigate the real scenario, their interactions inform the virtual scenario in real-time, allowing for immediate adjustments and refinements. This paper evaluates this framework and seeks to determine if human factors can be used to evaluate assistive products and if non-BVI users, when deprived of their vision, can similarly evaluate assistive devices as BVI users. The proposed framework seeks to elevate the practical utility of assistive devices and to include the users in the design process.

Article 2025

Adapted Methodology for Aerospace Sealant Inspection Using Neural Networks

Silva, Caroline C.D. , Fonseca, André R. , Lima, Carolina R. , Villani, Emilia , Mello, João M.G. , Cunha, Denizete B. , Farias, Marcelo , Braga, Thyago S.

AIAA Aviation Forum and Ascend 2025
Show abstract

© 2025 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.This study presents a novel deep learning-based method for inspecting aerospace sealants, utilizing a modified Mask Region-Based Convolutional Neural Network (Mask RCNN) for defect detection and segmentation. Inspired by medical image analysis techniques, the methodology involves training the modified Mask RCNN model to detect and classify defects in aerospace sealants, such as bubbles, cracks, and irregular application patterns. Several images of sealant applied to various surfaces are used for training, with data augmentation techniques enhancing the dataset to ensure robust performance under diverse conditions. Once trained, the model automatically generates detailed reports that highlighting the professional roles involved. The proposed method aims to improve maintenance efficiency, reduce human error, and ensure the quality of aerospace sealants, ultimately contributing to the overall safety and performance of aerospace components.

Article 2024

A novel approach to runway overrun risk assessment using FRAM and flight data monitoring

Reiser, C. , Villani, E. , Machado Cardoso-Junior, M.

Aeronautical Journal , vol. 128 (1327) , pp. 2054-2072
Citations: 2
Show abstract

© The Author(s), 2024.Runway overruns (ROs) are the result of an aircraft rolling beyond the end of a runway, which is one of the accident’s types that most frequently occurs on aviation. The risk of an RO arises from the synergistic effect among its precursors, such as unstable approaches, long touchdowns and inadequate use of deceleration devices. To analyse this complex socio-technical system, the current work proposes a customised functional resonance analysis method, called FRAM-FDM, as traditional techniques of risk and safety assessment do not identify the interactions and couplings between the various functional aspects of the system itself, especially regarding human and organisational components. Basically, FRAM-FDM is the coupling of a traditional FRAM with flight data monitoring (FDM) techniques, used here to quantify the variabilities of the flight crew performance while executing the required activity (i.e. the landing). In this proposal, these variabilities (i.e. the FRAM functions aspects) are aggregated by the addend of a logistic regression, resulting in a model to evaluate the flare operations and the brake application profile effect on the remaining distance to the end of the runway, used as a reference to classify the landing as acceptable or not. The present application of the FRAM-FDM assesses the operational risk of a sample fleet in overrunning the runway during landing, highlighting the brake pedal application profile as the most relevant contributor. The model improves the knowledge about the system behaviour, being useful to direct flight crew training.

Article 2024

Framework for Offline Data-Driven Aircraft Fault Diagnosis

Kraemer, Aline Dahleni , Villani, Emilia

Journal of Aerospace Information Systems , vol. 21 (4) , pp. 348-361
Citations: 3
Show abstract

© 2024 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.This paper proposes a framework for aircraft fault diagnosis based on the offline analysis of flight data. It overcomes the limitations of current data-driven approaches by combining steps based on both real data, obtained from aircraft flight data records, and simulated data, generated from aircraft models. The framework explores unsupervised and supervised methods, resulting in a proactive approach to flight safety and speeding the learning of fault cases. The influence of both temporal data representation and sensor selection on fault diagnosis performance is analyzed. The framework is organized into four phases (initial, training, operation, and improvement) that cover the aircraft system lifecycle. We used the hierarchical clustering algorithm in the unsupervised part and an ensemble of three algorithms (k-nearest neighbors, decision trees, and neural networks) in the supervised one. The framework is evaluated using an aircraft electrohydraulic actuating system as the case study, for which we obtained a balanced accuracy of 96% in the operation phase and of 90.4% in the improvement phase. The contribution of the framework is also accessed through a comparison with results obtained using only supervised methods. It confirms that the combination of supervised and unsupervised methods improves the performance of the fault diagnosis system.

Article 2024

A Safety-Oriented Motion Cueing Algorithm for a Serial Robotic Flight Simulator Using a Predictive Neural Network Reference Governor

Da C. Matheus, Aline , De Oliveira, Wesley R. , Villani, Emilia

IEEE Transactions on Intelligent Transportation Systems , vol. 25 (11) , pp. 15718-15731
Citations: 1
Show abstract

© 2024 IEEE.High fidelity flight simulators use motion platforms to reproduce the feeling of motion from a real flight. While most of the published works for both aircraft and vehicle simulators are related to parallel motion platforms, this work approaches the problem of designing the motion cueing algorithm of a flight simulator based on a serial manipulator. The simulator presents a large cockpit with an embedded visual system and dimensions that resemble those of an aircraft flight deck. Motion cueing in this context should be able to minimize false cues while ensuring safe operation, coping not only with the dynamic and kinematic constraints of the robot but also avoiding crash events that might happen between the cockpit and the serial arm. While there have been several contributions regarding classical filtering, tuning optimization, and model-based predictive control approaches to cope with constraints of parallel platforms, they result in the inefficient utilization of the robot workspace or even the inability to handle collisions of the cockpit with the robot. This work presents a novel motion cueing algorithm for a serial robotic flight simulator, which focuses on ensuring safety regarding the physical boundaries of the cockpit while enhancing motion fidelity. The approach is based on a hybrid model-based predictor that uses a neural network to infer workspace collisions in real-time (including crash events of the cockpit with the robotic arm), releasing a non-linear deterministic control action that acts as a feedforward reference governor. Simulation and experimental results evince improved workspace usage while ensuring safe operation.

Article 2024

A SYSTEMATIC REVIEW OF HUMAN FACTORS AND AI INFLUENCING OPERATOR PERFORMANCE IN MUM-T ENVIRONMENTS

Rehder, Ivan de Souza , Cardoso, Moacyr Machado , Villani, Emilia

Icas Proceedings
Citations: 1
Show abstract

© 2024, International Council of the Aeronautical Sciences. All rights reserved.This paper conducts a systematic quantitative literature review exploring the interplay between human factors and artificial intelligence (AI) in Manned-Unmanned Teaming (MUM-T) contexts. With AI’s rapid advancement and its growing role in military operations, especially in UAV management, a deeper understanding of how human cognitive capabilities intersect with AI is crucial. This review meticulously evaluates the existing body of literature, following a methodical process of gathering information, building a database, and generating a thorough analysis. The results of this review are organized into principal thematic areas, including levels of autonomy, the dynamics of trust in human-machine interactions, cognitive workload management, experimental practices, and analysis of human factors. The findings underscore the intricacies of integrating AI with human operators in MUM-T scenarios, revealing both challenges and opportunities. This comprehensive literature overview aims not only to synthesize current knowledge but also to guide future research and development in the domain, underlining the need for strategies that effectively marry AI capabilities with human expertise in complex military operations.

Article 2024

MULTIPLATFORM SIMULATION USING ROS

da Silva, Caroline Cristine Duarte , Castro, Yasmin , Sarmento, Andrew , Villani, Emilia

Icas Proceedings
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© 2024, International Council of the Aeronautical Sciences. All rights reserved.Robotics is a constantly evolving field that benefits from the use of tools powerful tools for robot development and simulation. Two of these tools, widely used ROS (Robot Operating System) and CoppeliaSim (formerly known as V-REP). ROS is an open-source framework widely used in the robotics community. On the other hand, CoppeliaSim is a simulation platform for powerful and versatile 3D robots. In this paper, we distributed an F16 simulation using ROS to create tasks, combining flight visualization by Flight Gear and collision analysis of a robotic flight simulator using CoppeliaSim.

Article 2024

FAULT DETECTION FOR AN AIRCRAFT ELEVATOR

Antoniazzi, Frederico Casara , Sarmento, Andrew Gomes Pereira , Villani, Emília

Icas Proceedings
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© 2024, International Council of the Aeronautical Sciences. All rights reserved.In aviation safety and performance play a pivotal role, and a critical theory part is fault detection, which can be used in subsystems that are important in ensuring the reliability of aircraft systems. This research delves into the implementation and testing of an architecture for fault detection using parity space methodology, specifically tailored to handle different maneuvers during the flight of an aircraft. The emphasis on maneuver-specific techniques aims to enhance fault detection’s overall robustness and accuracy in dynamic flight conditions. This work is intended to study two different forms of implementation for detecting faults in the actuator system of an aircraft, they will be tested using two actuator models for the elevator in a simple maneuver during the flight.

Article 2024

ASSESSING MENTAL WORKLOAD AND INTERFACE USABILITY IN MILITARY PILOTS: AN ADVANCED EYE-TRACKING METHODOLOGY

Russo, A. C. , Sarmento, A. , Rehder, I. S. , Cardoso-Junior, M. M. , Villani, E.

Icas Proceedings
Show abstract

© 2024, International Council of the Aeronautical Sciences. All rights reserved.This study explores the cognitive and ergonomic aspects of military UAV operations, focusing on pilots' mental workload and interface usability using advanced eye-tracking technology. A total of 24 military pilots participated in 30-minute flight simulations, with their eye movements recorded by Tobii Pro Glasses 2 and analyzed using Tobii Pro Lab software. Pilots' subjective perceptions of workload and interface usability were assessed through NASA-TLX and SUS questionnaires. Statistical analyses, including Pearson correlation, ANOVA, and linear regression, were conducted to examine the relationships between eye-tracking metrics (fixation duration, saccade amplitude, blink rate, and pupil dilation) and subjective assessments. The findings indicate that experienced pilots rated UAV interfaces as more usable, and higher mental workload, indicated by NASA-TLX scores, was strongly correlated with increased pupil dilation and blink rate. These results demonstrate the value of integrating eye-tracking technology with subjective assessments to achieve a comprehensive understanding of UAV operator interactions. The insights gained can inform the design of more intuitive and efficient UAV interfaces and training programs, enhancing operational safety and efficiency. This study contributes significantly to military aviation training and interface design, emphasizing the necessity of incorporating technological advancements with human factors to optimize UAV operations.

Supervisions (27 master's, 9 phd)

27
Master's Dissertations
9
PhD Theses
36
As Advisor
2
As Co-advisor

Ana Angélica da Costa Marchiori (2022) Master's

Manuel Alejandro Rodriguez Diaz (2022) PhD