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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 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.

2023

Estimation of Sediments in Underwater Wall Corners using a Mechanical Scanning Sonar

Authors
Goncalves, CF; Cruz, NA; Ferreira, BM;

Publication
2023 IEEE UNDERWATER TECHNOLOGY, UT

Abstract
This paper describes a robotic system to detect and estimate the volume of sediments in underwater wall corners, in scenarios with zero visibility. All detection and positioning is based on data from a scanning sonar. The main idea is to scan the walls and the bottom of the structure to detect the corner, and then use data obtained in the direction of the corner to estimate the presence of sediment accumulation and its volume. Our approach implements an image segmentation to extract range from the surfaces of interest. The resulting data is then employed for relative localization and estimate of the sediment accumulation. The paper provides information about the methodologies developed and data from practical experiments.

2023

Single Receiver Underwater Localization of an Unsynchronized Periodic Acoustic Beacon Using Synthetic Baseline

Authors
Ferreira, BM; Graça, PA; Alves, JC; Cruz, NA;

Publication
IEEE JOURNAL OF OCEANIC ENGINEERING

Abstract
This article addresses the 3-D localization of a stand-alone acoustic beacon based on the Principle of Synthetic Baseline using a single receiver on board a surface vehicle. The process only uses the passive reception of an acoustic signal with no explicit synchronization, interaction, or communication with the acoustic beacon. The localization process exploits the transmission of periodic signals without synchronization to a known time reference to estimate the time-of-arrival (ToA) with respect to an absolute time basis provided by the global navigation satellite system (GNSS). We present the development of the acoustic signal acquisition system, the signal processing algorithms, the data processing of times-of-arrival, and an estimator that uses times-of-arrival and the coordinates where they have been collected to obtain the 3-D position of the acoustic beacon. The proposed approach was validated in a real field application on a search for an underwater glider lost in September 2021 near the Portuguese coast.

Supervised
thesis

2023

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

Author
João Henrique Torres Santos

Institution
UP-FEUP

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

2022

Mapeamento e Localização Subaquática em Mapas Densos

Author
Paulo Miguel Alves Gonçalves

Institution
UP-FEUP

2022

Information-aware Feature-based Underwater Localization and Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP