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About

Aníbal Matos received a PhD in Electrical and Computer Engineering form Porto University in 2001. He is currently associate professor at the Faculty of Engineering of Porto University and a member of the board of directors at INESC TEC. 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

032
Publications

2022

3DupIC: An Underwater Scan Matching Method for Three-Dimensional Sonar Registration

Authors
Ferreira, A; Almeida, J; Martins, A; Matos, A; Silva, E;

Publication
SENSORS

Abstract
This work presents a six degrees of freedom probabilistic scan matching method for registration of 3D underwater sonar scans. Unlike previous works, where local submaps are built to overcome measurement sparsity, our solution develops scan matching directly from the raw sonar data. Our method, based on the probabilistic Iterative Correspondence (pIC), takes measurement uncertainty into consideration while developing the registration procedure. A new probabilistic sensor model was developed to compute the uncertainty of each scan measurement individually. Initial displacement guesses are obtained from a probabilistic dead reckoning approach, also detailed in this document. Experiments, based on real data, demonstrate superior robustness and accuracy of our method with respect to the popular ICP algorithm. An improved trajectory is obtained by integration of scan matching updates in the localization data fusion algorithm, resulting in a substantial reduction of the original dead reckoning drift.

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

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.

2021

Evaluation of Bags of Binary Words for Place Recognition in Challenging Scenarios

Authors
Gaspar, AR; Nunes, A; Matos, A;

Publication
2021 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)

Abstract
To perform autonomous tasks, robots in real-world environments must be able to navigate in dynamic and unknown spaces. To do so, they must recognize previously seen places to compensate for accumulated positional deviations. This task requires effective identification of recovered landmarks to produce a consistent map, and the use of binary descriptors is increasing, especially because of their compact representation. The visual Bag-of-Words (BoW) algorithm is one of the most commonly used techniques to perform appearance-based loop closure detection quickly and robustly. Therefore, this paper presents a behavioral evaluation of a conventional BoW scheme based on Oriented FAST and Rotated BRIEF (ORB) features for image similarity detection in challenging scenarios. For each scenario, full-indexing vocabularies are created to model the operating environment and evaluate the performance for recognizing previously seen places similar to online approaches. Experiments were conducted on multiple public datasets containing scene changes, perceptual aliasing conditions, or dynamic elements. The Bag of Binary Words technique shows a good balance to deal with such severe conditions at a low computational cost. © 2021 IEEE.

Supervised
thesis

2021

Visually Perceiving Symbolic Representation for Manipulation Task in Robotics

Author
Leandro Cardoso Pereira

Institution
UP-FEUP

2021

Business Diplomacy Relevance in Successful International Endeavours of MNCs: A Multiple Case Study Analysis.

Author
Rui Manuel Ribeiro Monteiro

Institution
UP-FEP

2021

O impacto do ruído no roteamento de veículos para a logística urbana

Author
CLÁUDIA SOFIA ELIAS MORAIS PEREIRA

Institution
IPP-ISEP

2021

Solving Sparse-Reward Problems in Robot Manipulation Tasks using Deep Reinforcement Learning

Author
Eduardo Miguel Lage Dixo Sousa

Institution
UP-FCUP

2021

Collaborative Tools for Lung Cancer Diagnosis in Computed Tomography

Author
Carlos Alexandre Nunes Ferreira

Institution
UP-FEUP