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Detalhes

018
Publicações

2020

Underwater Localization System Combining iUSBL with Dynamic SBL in ¡VAMOS! Trials

Autores
Almeida, J; Matias, B; Ferreira, A; Almeida, C; Martins, A; Silva, E;

Publicação
Sensors

Abstract
Emerging opportunities in the exploration of inland water bodies, such as underwater mining of flooded open pit mines, require accurate real-time positioning of multiple underwater assets. In the mining operation scenarios, operational requirements deny the application of standard acoustic positioning techniques, posing additional challenges to the localization problem. This paper presents a novel underwater localization solution, implemented for the ¡VAMOS! project, based on the combination of raw measurements from a short baseline (SBL) array and an inverted ultrashort baseline (iUSBL). An extended Kalman filter (EKF), fusing IMU raw measurements, pressure observations, SBL ranges, and USBL directional angles, estimates the localization of an underwater mining vehicle in 6DOF. Sensor bias and the speed of sound in the water are estimated indirectly by the filter. Moreover, in order to discard acoustic outliers, due to multipath reflections in such a confined and cluttered space, a data association layer and a dynamic SBL master selection heuristic were implemented. To demonstrate the advantage of this new technique, results obtained in the field, during the ¡VAMOS! underwater mining field trials, are presented and discussed.

2019

3D UNDERWATER MINE MODELLING in the ¡vAMOS! PROJECT

Autores
Bleier, M; Almeida, C; Ferreira, A; Pereira, R; Matias, B; Almeida, J; Pidgeon, J; van der Lucht, J; Schilling, K; Martins, A; Silva, E; Nuechter, A;

Publicação
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Abstract
The project Viable Alternative Mine Operating System (¡VAMOS!) develops a novel underwater mining technique for extracting inland mineral deposits in flooded open-cut mines. From a floating launch and recovery vessel a remotely-operated underwater mining vehicle with a roadheader cutting machine is deployed. The cut material is transported to the surface via a flexible riser hose. Since there is no direct intervisibility between the operator and the mining machine, the data of the sensor systems can only be perceived via a computer interface. Therefore, part of the efforts in the project focus on enhancing the situational awareness of the operator by providing a 3D model of the mine combined with representations of the mining equipment and sensor data. We present a method how a positioning and navigation system, perception system and mapping system can be used to create a replica of the physical system and mine environment in Virtual Reality (VR) in order to assist remote control. This approach is beneficial because it allows visualizing different sensor information and data in a consistent interface, and enables showing the complete context of the mining site even if only part of the mine is currently observed by surveying equipment. We demonstrate how the system is used during tele-operation and show results achieved during the field trials of the complete system in Silvermines, Ireland. © 2019 Copernicus GmbH. All righhts reserved.

2018

Supervised classification for hyperspectral imaging in UAV maritime target detection

Autores
Freitas, S; Almeida, C; Silva, H; Almeida, J; Silva, E;

Publicação
18th IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2018

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. © 2018 IEEE.

2018

EVA a hybrid ROV/AUV for underwater mining operations support

Autores
Martins, A; Almeida, J; Almeida, C; Matias, B; Kapusniak, S; Silva, E;

Publicação
2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018

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 ¡VAMOS! 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 © 2018 IEEE

2018

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

Autores
Almeida, J; Martins, A; Almeida, C; Dias, A; Matias, B; Ferreira, A; Jorge, P; Martins, R; Bleier, M; Nuechter, A; Pidgeon, J; Kapusniak, S; Silva, E;

Publicação
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Abstract