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About

Aníbal Matos received a PhD in Electrical and Computer Engineering form Porto University in 2001. He is currently coordinator of the Centre for Robotics and Autonomous Systems at INESC TEC and also an assistant professor at the Faculty of Engineering of Porto University. His main research interests are related to perception, sensing, navigation, and control of autonomous marine robots, being the author or co-author of more than 80 publications in international journals and conferences. He has participated and lead several research projects on marine robotics and its application to monitoring, inspection, search and rescue, and defense.

Interest
Topics
Details

Details

030
Publications

2021

Multi-domain inspection of offshore wind farms using an autonomous surface vehicle

Authors
Campos, DF; Matos, A; Pinto, AM;

Publication
SN Applied Sciences

Abstract
AbstractThe offshore wind power industry is an emerging and exponentially growing sector, which calls to a necessity for a cyclical monitoring and inspection to ensure the safety and efficiency of the wind farm facilities. Thus, the emersed (aerial) and immersed (underwater) scenarios must be reconstructed to create a more complete and reliable map that maximizes the observability of all the offshore structures from the wind turbines to the cable arrays, presenting a multi domain scenario.This work proposes the use of an Autonomous Surface Vehicle (ASV) to map both domains simultaneously. As such, it will produce a multi-domain map through the fusion of navigational sensors, GPS and IMU, to localize the vehicle and aid the registration process for the perception sensors, 3D Lidar and Multibeam echosounder sonar. The performed experiments demonstrate the ability of the multi-domain mapping architecture to provide an accurate reconstruction of both scenarios into a single representation using the odometry system as the initial seed to further improve the map with data filtering and registration processes. An error of 0.049 m for the odometry estimation is observed with the GPS/IMU fusion for simulated data and 0.07 m for real field tests. The multi-domain map methodology requires an average of 300 ms per iteration to reconstruct the environment, with an error of at most 0.042 m in simulation.

2021

Project and Control Allocation of a 3 DoF Autonomous Surface Vessel With Aerial Azimuth Propulsion System

Authors
da Silva, MF; Honorio, LMD; dos Santos, MF; Neto, AFD; Cruz, NA; Matos, ACC; Westin, LGF;

Publication
IEEE ACCESS

Abstract
To gather hydrological measurements is a difficult task for Autonomous Surface Vessels. It is necessary for precise navigation considering underwater obstacles, shallow and fast water flows, and also mitigate misreadings due to disturbs caused by their propulsion system. To deal with those problems, this paper presents a new topology of an Autonomous Surface Vessel (ASV) based on a catamaran boat with an aerial propulsion system with azimuth control. This set generates an over-actuated 3 Degree of Freedom (DoF) ASV, highly maneuverable and able of operating over the above-mentioned situations. To deal with the high computational cost of the over-actuated control allocation (CA) problem, this paper also proposes a Fast CA (FCA) approach. The FCA breaks the initial nonlinear system into partially-dependent linear subsystems. This approach generates smaller connected systems with overlapping solution spaces, generating fast and robust convergence, especially attractive for embedded control devices. Both proposals, i.e., ASV and FCA, are assessed through mathematical simulations and real scenarios.

2020

Deep Learning for Underwater Visual Odometry Estimation

Authors
Teixeira, B; Silva, H; Matos, A; Silva, E;

Publication
IEEE Access

Abstract

2020

MARESye: A hybrid imaging system for underwater robotic applications

Authors
Pinto, AM; Matos, AC;

Publication
INFORMATION FUSION

Abstract
This article presents an innovative hybrid imaging system that provides dense and accurate 3D information from harsh underwater environments. The proposed system is called MARESye and captures the advantages of both active and passive imaging methods: multiple light stripe range (LSR) and a photometric stereo (PS) technique, respectively. This hybrid approach fuses information from these techniques through a data-driven formulation to extend the measurement range and to produce high density 3D estimations in dynamic underwater environments. This hybrid system is driven by a gating timing approach to reduce the impact of several photometric issues related to the underwater environments such as, diffuse reflection, water turbidity and non-uniform illumination. Moreover, MARESye synchronizes and matches the acquisition of images with sub-sea phenomena which leads to clear pictures (with a high signal-to-noise ratio). Results conducted in realistic environments showed that MARESye is able to provide reliable, high density and accurate 3D data. Moreover, the experiments demonstrated that the performance of MARESye is less affected by sub-sea conditions since the SSIM index was 0.655 in high turbidity waters. Conventional imaging techniques obtained 0.328 in similar testing conditions. Therefore, the proposed system represents a valuable contribution for the inspection of maritime structures as well as for the navigation procedures of autonomous underwater vehicles during close range operations.

2020

MViDO: A high performance monocular vision-based system for docking a hovering AUV

Authors
Figueiredo, AB; Matos, AC;

Publication
Applied Sciences (Switzerland)

Abstract
This paper presents a high performance (low computationally demanding) monocular vision-based system for a hovering Autonomous Underwater Vehicle (AUV) in the context of autonomous docking process-MViDO system: Monocular Vision-based Docking Operation aid. The MViDO consists of three sub-modules: a pose estimator, a tracker and a guidance sub-module. The system is based on a single camera and a three spherical color markers target that signal the docking station. The MViDO system allows the pose estimation of the three color markers even in situations of temporary occlusions, being also a system that rejects outliers and false detections. This paper also describes the design and implementation of the MViDO guidance module for the docking manoeuvres. We address the problem of driving the AUV to a docking station with the help of the visual markers detected by the on-board camera, and show that by adequately choosing the references for the linear degrees of freedom of the AUV, the AUV is conducted to the dock while keeping those markers in the field of view of the on-board camera. The main concepts behind the MViDO are provided and a complete characterization of the developed system is presented from the formal and experimental point of view. To test and evaluate the MViDO detector and pose an estimator module, we created a ground truth setup. To test and evaluate the tracker module we used the MARES AUV and the designed target in a four-meter tank. The performance of the proposed guidance law was tested on simulink/Matlab. © 2020 by the authors.

Supervised
thesis

2020

Monocular vision-based system for docking a hovering AUV

Author
André Bianchi de Aguiar Araújo Figueiredo

Institution
UP-FEUP

2020

Active Cooperative Perception for UAVs Teams

Author
Guilherme Marques Amaral Silva

Institution
UP-FEUP

2020

Underwater 3D reconstruction and reinforcement of machine learning in object recognition

Author
Alexandra Pereira Nunes

Institution
UP-FEUP

2020

Modelação e controlo de um sistema robótico multicorpo interconectado

Author
Gonçalo Gil Seixas Rodrigues de Carvalho

Institution
UP-FEUP

2020

Modelação e simulação de um sistema robótico multicorpo interconectado

Author
Gonçalo Gil Seixas Rodrigues de Carvalho

Institution
UP-FEUP