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Sobre

Sobre

Aníbal Matos concluiu o doutoramento em Engenharia Electrotécnica e de Computadores pela Universidade do Porto em 2001. É atualmente professor associado na Faculdade de Engenharia da Universidade do Porto e membro do Conselho de Administração do INESC TEC. Os seus interesses principais de investigação são perceção, navegação e controlo de veículos robóticos aquáticos, sendo autor ou coautor de mais de 80 publicações em revistas e conferências internacionais. Tem participado e liderado projetos de investigação em robótica aquática e nas suas aplicações em monitorização, inspeção, busca e salvamento e defesa.

Tópicos
de interesse
Detalhes

Detalhes

032
Publicações

2022

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

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

Publicação
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

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

Publicação
OCEANS 2022

Abstract

2022

Modular Multi-Domain Aware Autonomous Surface Vehicle for Inspection

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

Publicação
IEEE ACCESS

Abstract

2021

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

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

Publicação
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

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

Publicação
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.

Teses
supervisionadas

2021

Data Privacy and the Value of Information.

Autor
Fábio Miguel Azevedo Correia

Instituição
UP-FEP

2021

Visually Perceiving Symbolic Representation for Manipulation Task in Robotics

Autor
Leandro Cardoso Pereira

Instituição
UP-FEUP

2021

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

Autor
Rui Manuel Ribeiro Monteiro

Instituição
UP-FEP

2021

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

Autor
CLÁUDIA SOFIA ELIAS MORAIS PEREIRA

Instituição
IPP-ISEP

2021

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

Autor
Eduardo Miguel Lage Dixo Sousa

Instituição
UP-FCUP