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- TURTLE – A robotic autonomous deep sea landerPublication . Silva, Eduardo; Martins, Alfredo; Soares Almeida, José Miguel; Ferreira, Hugo; Valente, António; Camilo, Maurício; Figueiredo, António; Pinheiro, CláudiaThis paper presents a new concept for a deep sea lander system combining both sea bottom permanence characteristics with autonomous repositioning functionalities and efficient ascent/descent motion in the water column. The TURTLE hybrid lander is a particular type of autonomous underwater vehicle designed to act as sea bottom fixed observation node or in operations of transport equipment to the deep sea. The paper discusses the general concept of operation and applications and also presents the developed prototype. This system was developed under a dual use EDA (European Defense Agency) project and with national and European funds. Considered as one of the dual use (civil and military) success stories, the demonstrator was equipped to sensors allowing both seismographic data gathering and acoustic monitoring applications.
- UAV Trials for Multi-Spectral Imaging Target Detection and Recognition in Maritime EnvironmentPublication . Silva, Hugo; Soares Almeida, José Miguel; Lopes, Flávio; Ribeiro, J.P.; Freitas, Sara; Amaral, Guilherme; Almeida, Carlos; Martins, Alfredo; Silva, EduardoThis paper addresses the use of heterogeneous sensors for target detection and recognition in maritime environment. An Unmanned Aerial Vehicle payload was assembled using hyperspectral, infrared, electro-optical, AIS and INS information to collect synchronized sensor data with vessel ground-truth position for conducting air and sea trials. The data collected is used to develop automated robust methods for detect and recognize vessels based on their exogenous physical characteristics and their behaviour across time. Data Processing preliminary results are also presented.
- Underwater Localization System Combining iUSBL with Dynamic SBL in ¡VAMOS! TrialsPublication . Almeida, José; Matias, Bruno; Ferreira, António João; Almeida, Carlos; Martins, Alfredo; Silva, EduardoEmerging 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.