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About

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

  • Name

    Bruno Miguel Ferreira
  • Role

    Senior Researcher
  • Since

    01st January 2010
011
Publications

2024

Probabilistic Positioning of a Mooring Cable in Sonar Images for In-Situ Calibration of Marine Sensors

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

Publication
IEEE TRANSACTIONS ON MOBILE COMPUTING

Abstract
The calibration of sensors stationed along a cable in marine observatories is a time-consuming and expensive operation that involves taking the mooring out of the water periodically. In this paper, we present a method that allows an underwater vehicle to approach a mooring, in order to take reference measurements along the cable for in-situ sensor calibration. We use the vehicle's Mechanically Scanned Imaging Sonar (MSIS) to identify the cable's reflection within the sonar image. After pre-processing the image to remove noise, enhance contour lines, and perform smoothing, we employ three detection steps: 1) selection of regions of interest that fit the cable's reflection pattern, 2) template matching, and 3) a track-before-detect scheme that utilized the vehicle's motion. The later involves building a lattice of template matching responses for a sequence of sonar images, and using the Viterbi algorithm to find the most probable sequence of cable locations that fits the maximum speed assumed for the surveying vessel. Performance is explored in pool and sea trials, and involves an MSIS onboard an underwater vehicle scanning its surrounding to identify a steel-core cable. The results show a sub-meter accuracy in the multi-reverberant pool environment and in the sea trial. For reproducibility, we share our implementation code.

2024

Autonomous Underwater Vehicle for System Identification Education

Authors
dos Santos, PL; Perdicoúlis, TPA; Ferreira, BM; Gonçalves, C;

Publication
IFAC PAPERSONLINE

Abstract
This paper advocates for the integration of system identification in graduate-level control system courses using accessible theoretical tools. Emphasising real-world applications, particularly in Remotely Operated Vehicle (ROV), the study proposes ROV as educational platforms for teaching control principles. As a concrete example, the paper presents a graduation course project focusing on designing a depth control system for an ROV, where students derive the model from experimental data. This practical application not only enhances the students skills in system identification but also prepares them for challenges in controlling complex systems in both academic and industrial settings.

2024

A Clustering-Aided Template Matching Algorithm Towards Underwater SLAM Using Imaging Sonar

Authors
Oliveira, J; Ferreira, M; Cruz, A;

Publication
Oceans Conference Record (IEEE)

Abstract
In man-made marine infrastructures, elements such as pillars, cables or ducts are common, which provide distinctive landmarks for Simultaneous Localization and Mapping purposes. In this work, we concentrate on the application of template matching to acoustic imagery for landmark detection and tracking, building on the modeling of common elements in marine environments. The proposed algorithm extends on the original method by employing a density-based clustering technique for match candidate selection and leveraging vehicle inertial information to identify regions of interest in the acquired images, tackling performance deterioration resulting from motion-induced image deformation and overall acoustic feature ambiguity. Experimental results are provided based on datasets collected in a testing pool environment. © 2024 IEEE.

2024

A Model Predictive Control Approach to Enhance Obstacle Avoidance While Performing Autonomous Docking

Authors
Pinto A.; Ferreira B.M.; Cruz N.; Soares S.P.; Cunha J.B.;

Publication
Oceans Conference Record (IEEE)

Abstract
In the present paper, we propose a control approach to perform docking of an autonomous surface vehicle (ASV) while avoiding surrounding obstacles. This control architecture is composed of two sequential controllers. The first outputs a feasible trajectory between the vessel's initial and target state while avoiding obstacles. This trajectory also minimizes the vehicle velocity while performing the maneuvers to increase the safety of onboard passengers. The second controller performs trajectory tracking while accounting for the actuator's physical limits (extreme actuation values and the rate of change). The method's performance is tested on simulation, as it enables a reliable ground truth method to validate the control architecture proposed.

2024

Real-Time Geo-Referenced Acoustic Tracking for Underwater Diver Localization with Event Detection

Authors
Villa, MP; Graca, A; Ferreira, M; Piga, A; Silveira, T; Segal, B; Cruz, N; Alves, JC; Crivellaro, M; Souza, R; Soldateli, M;

Publication
Oceans Conference Record (IEEE)

Abstract
This paper investigates the real-time tracking capabilities of the Long Baseline (LBL) acoustic tracking system, developed by INESC TEC, for near-shore monitoring applications with human divers. The study aims to determine the system's suitability for environmental monitoring under challenging conditions, such as very shallow water and areas close to the coastline, where acoustic multipath effects are prevalent and can cause significant measurement errors. To mitigate these errors, a two-stage outlier rejection algorithm was implemented. The algorithm's performance was evaluated by comparing the measurement data at each stage and assessing the reduction in erroneous readings. The tracking performance was evaluated based on accuracy and repeatability. Two dives were performed, during which positions marked using the developed system were compared with GNSS data. © 2024 IEEE.

Supervised
thesis

2023

Information-aware Feature-based Underwater Localization and Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP

2023

Dynamic Reconfiguration of Underwater Acoustic Systems for Enhanced Localization via Active Perception

Author
Paula Alexandra Agra Graça

Institution
UP-FEUP

2023

Multi-sensor fusion for precise state estimation applied to docking of marine surface vehicles

Author
João Henrique Torres Santos

Institution
UP-FEUP

2022

Information-aware Feature-based Underwater Localization and Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP

2022

Mapeamento e Localização Subaquática em Mapas Densos

Author
Paulo Miguel Alves Gonçalves

Institution
UP-FEUP