Showing papers by "Eduardo Silva published in 2018"

UX 1 system design - A robotic system for underwater mining exploration

Abstract: This paper describes the UX-l underwater mine exploration robotic system under development in the context of the UNEXMIN project. UNEXMIN is an international innovation action funded under the EU H2020 program, aiming to develop new technologies and services allowing the exploration of flooded underaround mines. The system is comprised by the UX-l robot prototype, launch and recovery system, command and control subsystem and a data management and post-processing computational infrastructure. The UX-l robot is a small spherical robot equipped with a multibeam sonar, five digital cameras and rotating laser line structured light systems. It is capable of obtaining an accurate point cloud of the surrounding environment along with high resolution imagery. A set of mineralogy, water parameters and geophysical sensors was also developed in order to obtain a more comprehensive mine model. These comprise a multi-spectral camera, electro-conductivity, pH, magnetic field sensors, a subbottom sonar, total natural gamma-ray detector, UV-light for fluorescent observation and a water samnling unit. The design of the system is presented along with the robot design. Some preliminary results are also presented and discussed

Hyperspectral Imaging for Real-Time Unmanned Aerial Vehicle Maritime Target Detection

Abstract: This work address hyperspectral imaging systems use for maritime target detection using unmanned aerial vehicles. Specifically, by working in the creation of a hyperspectral real-time data processing system pipeline. We develop a boresight calibration method that allows to calibrate the position of the navigation sensor related to the camera imaging sensor, and improve substantially the accuracy of the target geo-reference. We also develop an unsupervised method for segmenting targets (boats) from their dominant background in real-time. We evaluated the performance of our proposed system for target detection in real-time with UAV flight data and present detection results comparing favorably our approach against other state-of- the-art method.

Should tumbling E go out of date in amblyopia screening? Evidence from a population-based sample normative in children aged 3-4 years

Abstract: Aims To determine a normative of tumbling E optotype and its feasibility for visual acuity (VA) assessment in children aged 3-4 years. Methods A cross-sectional study of 1756 children who were invited to participate in a comprehensive non-invasive eye exam. Uncorrected monocular VA with crowded tumbling E with a comprehensive ophthalmological examination were assessed. Testability rates of the whole population and VA of the healthy children for different age subgroups, gender, school type and the order of testing in which the ophthalmological examination was performed were evaluated. Results The overall testability rate was 95% (92% and 98% for children aged 3 and 4 years, respectively). The mean VA of the first-day assessment (first-VA) and best-VA over 2 days’ assessments was 0.14 logMAR (95% CI 0.14 to 0.15) (decimal=0.72, 95% CI 0.71 to 0.73) and 0.13 logMAR (95% CI 0.13 to 0.14) (decimal=0.74, 95% CI 0.73 to 0.74). Analysis with age showed differences between groups in first-VA (F(3,1146)=10.0; p Conclusions This is the first normative for European Caucasian children with single crowded tumbling E in healthy eyes and the largest study comparing 3 and 4 years old testability. Testability rates are higher than found in literature with other optotypes, especially in children aged 3 years, where we found 5%–11% better testability rates.

ίVAMOS! Underwater Mining Machine Navigation System

Abstract: Limited perception capabilities underwater shrink the envelope of effective localization techniques that can be applied in this environment. Long-term localization in six degrees of freedom can only be achieved by combining different sources of information. A multiple vehicle underwater localization solution, for localizing an underwater mining vehicle and its support vessel, is presented in this paper. The surface vessel carries a short baseline network, that interact with the inverted ultra-short baseline, carried by the underwater mining vehicle. A multiple antenna GNSS system provides data for localizing the surface vessel and to georeference the short baseline array. Localization of the mining vehicle results from a data fusion approach, that combines multiple sources of sensor information using the Extended Kalman Filter (EKF) framework. The developed solutions were applied in the context of the iVAMOS! European project. Long-term real time position errors below 0.2 meters, for the underwater machine, and 0.02 meters, for the surface vessel, were accomplished in the field. All presented results are based on data acquired in a real scenario.

EVA a Hybrid ROV/AUV for Underwater Mining Operations Support

Abstract: This paper presents EVA, a new concept for an hybrid ROV/AUV designed to support the underwater operation of an underwater mining machine, developed in the context of the European H2020 R&D iVAMOS! Project. This project is briefly presented, introducing the main components and concepts, providing the reader with clear picture of the operational scenario and allowing to understand better the functionality requirements of the support robotic vehicle developed. The design of EVA is detailed presented, addressing the mechanical design, hardware architecture, sensor system and navigation and control. The results of EVA both in water test tank, in the !VAMOS! Field trials in Lee Moor, UK, and in an harbor scenario are presented and discussed

New pediatric risk factors for amblyopia: strabismic versus refractive.

Abstract: Purpose:To assess the role of risk factors for amblyopia, such as family history and neonatal background, for the prediction of either strabismic amblyopia or refractive amblyopia.Methods:In this r...

Supervised classification for hyperspectral imaging in UAV maritime target detection

Abstract: This paper addresses the use of a hyperspectral image system to detect vessels in maritime operational scenarios. The developed hyperspectral imaging classification methods are based on supervised approaches and allow to detect the presence of vessels using real hyperspectral data. We implemented two different methods for comparison purposes: SVM and SAM. The SVM method, which can be considered one of most utilized methods for image classification, was implemented using linear, RBF, sigmoid and polynomial kernels with PCA for dimensionality reduction, and compared with SAM using a two classes definition, namely vessel and water. The obtained results using real data collected from a UAV allow to conclude that the SVM approach is suitable for detecting the vessel presence in the water with a precision and recall rates favorable when compared to SAM.

Control-Law for Oil Spill Mitigation with an Autonomous Surface Vehicle

Abstract: Oil spill incidents in the sea or harbors occur with some regularity during exploration, production, and transport of petroleum products. In order to mitigate the impact of the oil spill in the marine life, immediate, safety, effective and eco-friendly actions must be taken. Autonomous vehicles can assume an important contribution by establishing a cooperative and coordinated intervention. This paper presents the development of a path planning control-law methods for an autonomous surface vehicle (ASV) being able to contour the oil spill while is deploying microorganisms and nutrients (bioremediation) capable of mitigating and contain the oil spill spread with the collaboration of a UAV vehicle. An oil spill simulation scenario was developed in Gazebo to support the evaluation of the cooperative actions between the ASV and UAV and to infer the ASV path planning for each one of the proposed control-law methods.

UXNEXMIN AUV Perception System Design and Characterization

Abstract: This paper presents the perception system designed for the underwater mine exploration UNEXMIN robot.This autonomous underwater vehicle was designed in the context of the European H2020 UNEXMIN project to explore flooded underground minesThe presented work addresses the sensor choice and placement options, the characterization of the system with results obtained in test tank and on field missions in mines. The perception software and computational architecture is also discussed with details on its distributed features. This perception system is comprised of one multibeam imaging/profiling sonar, one mechanically scanning sonar, 5 digital cameras and a set of custom developed laser based structured light systems.The presented results from the Kaatiala mine (Finland) field trials and the Idrija mine tests (Slovenia) are discussed and allow for the performance analysis of the system.

Positioning. Navigation and Awareness of the !VAMOS! Underwater Robotic Mining System

Abstract: This paper presents the positioning, navigation and awareness (PNA) system developed for the Underwater Robotic Mining System of the !VAMOS! project [1]. It describes the main components of the !VAMOS! system, the PNA sensors in each of those components, the global architecture of the PNA system, and its main subsystems: Position and Navigation, Realtime Mine Modeling, 3D Virtual reality HMI and Real-time grade system. General results and lessons learn during the first mining field trial in Lee Moor, Devon, UK during the months of September and October 2017 are presented.

Supervised vs Unsupervised Approaches for Real Time Hyperspectral Imaging Maritime Target Detection

Abstract: This paper addresses the use of supervised and unsupervised methods for classification of hyperspectral imaging data in maritime border surveillance domain. In this work supervised (SVM) and unsupervised (HYDADE) approaches were implemented. An evaluation benchmark was performed in order to compare methods results using real hyperspectral imaging data taken from an Unmanned Aerial Vehicle in maritime border surveillance scenario.

Underwater Acoustic Signal Detection and Identification Study for Acoustic Tracking Applications

Abstract: In this work an acoustic tag detector was developed for the integration in a mobile robotic fish tracking architecture. The present paper presents both the developed system and preliminary results with particular emphasis of the developed solution with the tag manufacturer receiver. The work has been developed in the context of the MYTAG Portuguese RD project, addressing the study and characterisation of the European flounder migrations in the northern estuarine environments of Portugal. The detector is to be integrated in a tracking system using autonomous surface vehicles and fixed buoys. The main objective is to detect tags inserted surgically in flounders for the MYTAG project, while simultaneously identifying them. A detector solution is presented allowing for the detection and identification of V7 VEMCO tags and preliminary comparative results with the commercially available manufacturer receivers are also presented and discussed.