2008
Autores
Silva, SR; Cunha, S; Matos, A; Cruz, N;
Publicação
OCEANS 2008, VOLS 1-4
Abstract
A new approach for synthetic aperture image formation is presented in this paper. With the presented method image formation is regarded as a signal arrangement that can be described by a matrix. This method integrates the sonar platform motion in the image formation process but more importantly it acknowledges the non ideal data gathering process and implements means to mitigate these shortcomings. This method is illustrated with real data obtained in test mission in the Douro River, Portugal by a synthetic aperture sonar developed at the University of Porto.
2008
Autores
Cruz, NA; Alves, JC;
Publicação
OGAI Journal (Oesterreichische Gesellschaft fuer Artificial Intelligence)
Abstract
In this paper, we discuss some of the potential applications of small scale autonomous sailboats. The use of autonomous sailboats for ocean sampling has been tentatively proposed before, but there have been minor efforts towards the development and deployment of actual prototypes, due to a number of technical limitations and significant risks of operation. We show that, currently, most of the limitations have been surpassed, with the existing availability of extremely low power electronics, flexible computational systems and high performance renewable power sources. At the same time, some of the major risks have been mitigated, allowing this emerging technology to become an effective tool for a wide range of applications in real scenarios. We illustrate some of these scenarios and we describe the status of the current efforts being made to develop operational prototypes, with some promising results already being achieved.
2008
Autores
Melo, J; Matos, A;
Publicação
OCEANS 2008, VOLS 1-4
Abstract
The following addresses the control of an Autonomous Surface Vehicle (ASV) to follow the trajectory made by an Autonomous Underwater Vehicle (AUV) when the last is performing any given pre-programmed mission. In fact, it has been proved to be of great interest to have an ASV that could follow on the surface and even catch up the trajectory performed by the AUV, when executing a given mission. In order to achieve this desired coordinated motion between AUV and ASV, it would make sense just to program each of the vehicles with the same mission. However, due to the nature of vehicles, missions and also due to the localization system used, with this kind of solution some problems would arise, namely related with timings and synchronization, which are indeed difficult to overcome. The solution proposed here tries to estimate the AUV position, by tapping the signals exchanged between the former and each of the beacons of the acoustic localization network, and control and actuate the ASV in accordance.
2008
Autores
Silva, H; Almeida, JM; Lima, L; Martins, A; Silva, EP;
Publicação
ROBOCUP 2007: ROBOT SOCCER WORLD CUP XI
Abstract
This paper propose a real-time vision framework for mobile robotics and describes the current implementation. The pipeline structure further reduces latency and allows a paralleled hardware implementation. A dedicated hardware vision sensor was developed in order to take advantage of the proposed architecture. The real-time characteristics and hardware partial implementation, coupled with low energy consumption address typical autonomous systems applications. A characterization of the implemented system in the Robocup scenario, during competition matches, is presented.
2008
Autores
Malheiro, B;
Publicação
Wiley Encyclopedia of Computer Science and Engineering
Abstract
2008
Autores
Barbosa, SM; Silva, ME; Fernandes, MJ;
Publicação
Lecture Notes in Earth Sciences
Abstract
The characterisation and quantification of long-term sea-level variability is of considerable interest in a climate change context. Long time series from coastal tide gauges are particularly appropriate for this purpose. Long-term variability in tide gauge records is usually expressed through the linear slope resulting from the fit of a linear model to the time series, thus assuming that the generating process is deterministic with a short memory component. However, this assumption needs to be tested, since trend features can also be due to non-deterministic processes such as random walk or long range dependent processes, or even be driven by a combination of deterministic and stochastic processes. Specific methodology is therefore required to distinguish between a deterministic trend and stochastically-driven trend-like features in a time series. In this chapter, long-term sea-level variability is characterised through the application of (i) parametric statistical tests for stationarity, (ii) wavelet analysis for assessing scaling features, and (iii) generalised least squares for estimating deterministic trends. The results presented here for long tide gauge records in the North Atlantic show, despite some local coherency, profound differences in terms of the low frequency structure of these sea-level time series. These differences suggest that the long-term variations are reflecting mainly local/regional phenomena. © 2008 Springer-Verlag Berlin Heidelberg.
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