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About

Concluí o Mestrado Integrado em Engenharia Eletrotécnica e de Computadores na Faculdade de Engenharia da Universidade do Porto, em Fevereiro de 2017. No culminar da minha formação, com a realização da dissertação de mestrado, iniciei a colaboração com o centro de Robótica e Sistemas (CRAS) do INESC TEC. A mesma teve como  objetivo o desenvolvimento de um sistema visual de navegação e mapeamento simultâneos em proximidade ao fundo do mar, com o desenvolvimento de um método de vocabulário visual online para reconhecimento de áreas revisitadas por parte dos veículos subaquáticos autónomos (AUV). Atualmente, desde Maio de 2017, sou bolseira do CRAS. Participei no projeto de um sistema de localização baseado em recetores GPS e sistema inercial e, neste momento, encontro-me envolvida na área de visão e 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

Simultaneous Underwater Navigation and Mapping

Authors
Gaspar, ARS; Matos, A;

Publication
U.Porto Journal of Engineering

Abstract
The use of underwater autonomous vehicles has been growing, allowing the performance of tasks that cause inherent risks to Human, namely in inspection processes near to structures. With growth in usage of systems with autonomous navigation, visual acquisition methods have also gotten more developed because, they have appealing cost and they also show interesting results when operate at a short distance. It is possible to improve the quality of navigation through visual SLAM techniques which can map and locate simultaneously and its key aspect is the detection of revisited areas. These techniques are not usually applied to underwater scenarios and, therefore, its performance in environment is unknown. The paper presents a more reliable navigation system for underwater vehicles, resorting to some visual SLAM techniques from literature. The results, conducted in a realistic scenario, demonstrated the ability of the system to be applied to underwater environment.

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