Detalhes
Nome
Carlos AlmeidaCluster
Redes de Sistemas InteligentesCargo
Investigador AuxiliarDesde
01 julho 2013
Nacionalidade
PortugalCentro
Centro de Robótica e Sistemas AutónomosContactos
+351228340554
carlos.almeida@inesctec.pt
2020
Autores
Almeida, J; Matias, B; Ferreira, A; Almeida, C; Martins, A; Silva, E;
Publicação
Sensors
Abstract
2019
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
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
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
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
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