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About

About

Hi! I am a Researcher at the Centre for Robotics and Autonomous Systems (CRAS) at INESC TEC with a PhD research scholarship from FCT. I received my master's degree in Electrical and Computer Engineering at the Faculty of Engineering of the University of Porto (FEUP), Portugal, in 2014. Since then I was involved in several R&D projects related to the development of service and industrial robots, both in industry and research centres. In 2018, I decided to apply to the Doctoral Program in Electrical and Computer Engineering at the Faculty of Engineering of the University of Porto (FEUP), Portugal, starting my collaboration with CRAS. Currently, my research interests include robotics, 3D multi-domain reconstructions of the environment, distributed perception and collision avoidance techniques, mainly focused on maritime robotics. For more information, check my CV in: https://cienciavitae.pt/portal/en/661B-6DD9-0B87

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Details

Details

002
Publications

2022

Modular Multi-Domain Aware Autonomous Surface Vehicle for Inspection

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

Publication
IEEE ACCESS

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

Automatic Program Repair as Semantic Suggestions: An Empirical Study

Authors
Campos, D; Restivo, A; Ferreira, HS; Ramos, A;

Publication
2021 14TH IEEE CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION (ICST 2021)

Abstract

2021

ATLANTIS - The Atlantic Testing Platform for Maritime Robotics

Authors
Pinto A.M.; Marques J.V.A.; Campos D.F.; Abreu N.; Matos A.; Jussi M.; Berglund R.; Halme J.; Tikka P.; Formiga J.; Verrecchia C.; Langiano S.; Santos C.; Sa N.; Stoker J.J.; Calderoni F.; Govindaraj S.; But A.; Gale L.; Ribas D.; Hurtos N.; Vidal E.; Ridao P.; Chieslak P.; Palomeras N.; Barberis S.; Aceto L.;

Publication
Oceans Conference Record (IEEE)

Abstract

2021

DIIUS - Distributed Perception for Inspection of Aquatic Structures

Authors
Campos D.F.; Pereira M.; Matos A.; Pinto A.M.;

Publication
Oceans Conference Record (IEEE)

Abstract
The worldwide context has fostered the innovation geared to the blue growth. However, the aquatic environment imposes many restrictions to mobile robots, as their perceptual capacity becomes severely limited. DIIUS aims to strengthen the perception of distributed robotic systems to improve the current procedures for inspection of aquatic structures (constructions and/or vessels).The perception of large working areas from multiples robots raises a number of unresolved inference problems and calls for new interaction patterns between multiple disciplines, both at the conceptual and technical level. To address this important challenge, the DIIUS project seeks to reinforce the current state-of-art in several scientific domains that fit into artificial intelligence, computer vision, and robotics. Through case studies focused on 3D mapping of aquatic structures (ex., maritime constructions and adduction tunnels), the project investigates new spatio-temporal data association techniques, including the correlation of sensors from heterogeneous robot formations operating in environments with communications constraints.