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About

I am a Senior Researcher at the center for Robotics and Autonomous Systems at INESC TEC. I graduated in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto, first with a MSc degree in 2009 and with a PhD degree in 2014. Since 2009, I have been working on Surface and Underwater Robotics, researching on Control, Guidance, Localization and Coordination of marine robots.

My activities have been developed in the context of several national and international projects, among which the following are highlighted: Lajeado (development of an AUV for dam inspection); FP7 ICARUS (Integrated Components for Assisted Rescue and Unmanned Search operations); and FLEXUS (Flexible Unmanned Surface vehicles for the Internet of moving things), funded by H2020 RAWFIE project.

I am also involved in the development of several robotic systems and at the origin of several prototypes such as the autonomous surface vehicle FLEXUS and the autonomous underwater vehicle SHAD.

Interest
Topics
Details

Details

012
Publications

2022

An Autonomous System for Collecting Water Samples from the Surface

Authors
Pinto, AF; Cruz, NA; Ferreira, BM; Abreu, NM; Goncalves, CE; Villa, MP; Matos, AC; Honorio, LD; Westin, LG;

Publication
OCEANS 2022

Abstract

2021

A Performance Analysis of Feature Extraction Algorithms for Acoustic Image-Based Underwater Navigation

Authors
Oliveira, AJ; Ferreira, BM; Cruz, NA;

Publication
JOURNAL OF MARINE SCIENCE AND ENGINEERING

Abstract
In underwater navigation, sonars are useful sensing devices for operation in confined or structured environments, enabling the detection and identification of underwater environmental features through the acquisition of acoustic images. Nonetheless, in these environments, several problems affect their performance, such as background noise and multiple secondary echoes. In recent years, research has been conducted regarding the application of feature extraction algorithms to underwater acoustic images, with the purpose of achieving a robust solution for the detection and matching of environmental features. However, since these algorithms were originally developed for optical image analysis, conclusions in the literature diverge regarding their suitability to acoustic imaging. This article presents a detailed comparison between the SURF (Speeded-Up Robust Features), ORB (Oriented FAST and Rotated BRIEF), BRISK (Binary Robust Invariant Scalable Keypoints), and SURF-Harris algorithms, based on the performance of their feature detection and description procedures, when applied to acoustic data collected by an autonomous underwater vehicle. Several characteristics of the studied algorithms were taken into account, such as feature point distribution, feature detection accuracy, and feature description robustness. A possible adaptation of feature extraction procedures to acoustic imaging is further explored through the implementation of a feature selection module. The performed comparison has also provided evidence that further development of the current feature description methodologies might be required for underwater acoustic image analysis.

2021

A Novel Simulation Platform for Underwater Data Muling Communications Using Autonomous Underwater Vehicles

Authors
Teixeira, FB; Ferreira, BM; Moreira, N; Abreu, N; Villa, M; Loureiro, JP; Cruz, NA; Alves, JC; Ricardo, M; Campos, R;

Publication
Comput.

Abstract
Autonomous Underwater Vehicles (AUVs) are seen as a safe and cost-effective platforms for performing a myriad of underwater missions. These vehicles are equipped with multiple sensors which, combined with their long endurance, can produce large amounts of data, especially when used for video capturing. These data need to be transferred to the surface to be processed and analyzed. When considering deep sea operations, where surfacing before the end of the mission may be unpractical, the communication is limited to low bitrate acoustic communications, which make unfeasible the timely transmission of large amounts of data unfeasible. The usage of AUVs as data mules is an alternative communications solution. Data mules can be used to establish a broadband data link by combining short-range, high bitrate communications (e.g., RF and wireless optical) with a Delay Tolerant Network approach. This paper presents an enhanced version of UDMSim, a novel simulation platform for data muling communications. UDMSim is built upon a new realistic AUV Motion and Localization (AML) simulator and Network Simulator 3 (ns-3). It can simulate the position of the data mules, including localization errors, realistic position control adjustments, the received signal, the realistic throughput adjustments, and connection losses due to the fast SNR change observed underwater. The enhanced version includes a more realistic AML simulator and the antenna radiation patterns to help evaluating the design and relative placement of underwater antennas. The results obtained using UDMSim show a good match with the experimental results achieved using an underwater testbed. UDMSim is made available to the community to support easy and faster evaluation of underwater data muling oriented communications solutions and to enable offline replication of real world experiments.

2021

Differential Pressure Speedometer for Autonomous Underwater Vehicle

Authors
Villa, MP; Ferreira, BM; Matos, AC;

Publication
OCEANS 2021: San Diego – Porto

Abstract

2021

Feature-based Underwater Localization using Imaging Sonar in Confined Environments

Authors
Oliveira, AJ; Ferreira, BM; Cruz, NA;

Publication
OCEANS 2021: San Diego – Porto

Abstract

Supervised
thesis

2021

Information-aware Feature-based Underwater Localization and Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP

2021

Underwater Localization in Complex Environments

Author
Maria Sara Delgadinho Noronha

Institution
UP-FEUP

2020

Control of an Autonomous Underwater Vehicle in 6 Degrees of Freedom

Author
José Francisco Saraiva Santos

Institution
UP-FEUP

2020

Guidance of an Autonomous Surface Vehicle for Underwater Navigation Aid

Author
José Pedro Martins Pires e Sousa

Institution
UP-FEUP

2020

Information-aware Feature-based Underwater Localization and Motion Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP