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About

Em Fevereiro de 2017 conclui o Mestrado Integrado em Engenharia Eletrotécnica e de Computadores na Faculdade de Engenharia da Universidade do Porto. A ligação ao Centro de Robótica e Sistemas (CRAS) iniciou-se aquando a realização da minha dissertação, cujo objetivo era  o mapeamento do fundo do mar bem como das estruturas subaquáticas nele presentes, utilizando um método de estimação de movimento visual. Desde Maio do mesmo ano, sou bolseira do CRAS. Estive envolvida no projeto de um sistema de localização baseado em recetores GPS e sistema inercial e, neste momento, a minha área de trabalho será focada na visão e a percepção.       

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Publications

2019

A mosaicking technique for object identification in underwater environments

Authors
Nunes, AP; Silva Gaspar, ARS; Pinto, AM; Matos, AC;

Publication
Sensor Review

Abstract
Purpose: This paper aims to present a mosaicking method for underwater robotic applications, whose result can be provided to other perceptual systems for scene understanding such as real-time object recognition. Design/methodology/approach: This method is called robust and large-scale mosaicking (ROLAMOS) and presents an efficient frame-to-frame motion estimation with outlier removal and consistency checking that maps large visual areas in high resolution. The visual mosaic of the sea-floor is created on-the-fly by a robust registration procedure that composes monocular observations and manages the computational resources. Moreover, the registration process of ROLAMOS aligns the observation to the existing mosaic. Findings: A comprehensive set of experiments compares the performance of ROLAMOS to other similar approaches, using both data sets (publicly available) and live data obtained by a ROV operating in real scenes. The results demonstrate that ROLAMOS is adequate for mapping of sea-floor scenarios as it provides accurate information from the seabed, which is of extreme importance for autonomous robots surveying the environment that does not rely on specialized computers. Originality/value: The ROLAMOS is suitable for robotic applications that require an online, robust and effective technique to reconstruct the underwater environment from only visual information. © 2018, Emerald Publishing Limited.

2019

Three-Dimensional Mapping in Underwater Environment

Authors
Nunes, AP; Matos, A;

Publication
U.Porto Journal of Engineering

Abstract
Autonomous underwater vehicles are applied in diverse fields, namely in tasks that are risky for human beings to perform, as optical inspection for the purpose of structures quality control. Optical sensors are more appealing cost and they supply a larger quantity of data. Lasers can be used to reconstruct structures in three dimensions, along with cameras, which create a faithful representation of the environment. However, in this context a visual approach was used and the paper presents a method that can put together the three-dimensional information that has been harvested over time, combining also RGB information for surface reconstruction. The map construction follows the motion estimated by a odometry method previously selected from the literature. Experiments conducted using real scenario show that the proposed solution is able to provide a reliable map for objects and even the seafloor.

2018

Comparative Study of Visual Odometry and SLAM Techniques

Authors
Gaspar, AR; Nunes, A; Pinto, A; Matos, A;

Publication
Advances in Intelligent Systems and Computing

Abstract
The use of the odometry and SLAM visual methods in autonomous vehicles has been growing. Optical sensors provide valuable information from the scenario that enhance the navigation of autonomous vehicles. Although several visual techniques are already available in the literature, their performance could be significantly affected by the scene captured by the optical sensor. In this context, this paper presents a comparative analysis of three monocular visual odometry methods and three stereo SLAM techniques. The advantages, particularities and performance of each technique are discussed, to provide information that is relevant for the development of new research and novel robotic applications. © Springer International Publishing AG 2018.

2018

Urban@CRAS dataset: Benchmarking of visual odometry and SLAM techniques

Authors
Gaspar, AR; Nunes, A; Pinto, AM; Matos, A;

Publication
Robotics and Autonomous Systems

Abstract