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About

Nuno Cruz holds a MSc. in Digital Systems Engineering from UMIST, UK, and a PhD. in Electrical Engineering from the University of Porto, in Portugal. He is currently an Assistant Professor at the Faculty of Engineering of the University of Porto and a Coordinator at the Centre for Robotics and Autonomous Systems at INESC TEC. Nuno Cruz is an Associate Editor of the IEEE Journal of Oceanic Engineering and has over 100 publications in journals and proceedings of international conferences. He has been involved in the development and deployment of marine robotic vehicles for more than 20 years. He has led the design of multiple autonomous vehicles at the University of Porto and INESC TEC, namely the Zarco and Gama ASVs and the MARES and TriMARES AUVs. His current research interests include the development of strategies for the efficient use of autonomous vehicles at sea, including the concept of adaptive sampling.

More info in http://oceansys.fe.up.pt/

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Details

018
Publications

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

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

Pneuma: entrepreneurial science in the fight against the COVID-19 pandemic - a tale of industrialisation and international cooperation

Authors
Mendonça, JM; Cruz, N; Vasconcelos, D; Sá-Couto, C; Moreira, AP; Costa, P; Mendonça, H; Pereira, A; Naimi, Z; Miranda, V;

Publication
Journal of Innovation Management

Abstract
When the COVID-19 pandemic hits Portugal in early March 2020, medical doctors, engineers and researchers, with the encouragement of the Northern Region Health Administration, teamed up to develop and build, locally and in a short time, a ventilator that might eventually be used in extreme emergency situations in the hospitals of northern Portugal. This letter tells you the story of Pneuma, a low-cost emergency ventilator designed and built under harsh isolation constraints, that gave birth to derivative designs in Brazil and Morocco, has been industrialized with 200 units being produced and is now looking forward to the certification as a medical device that will possibly support a go-to-market launch. Open intellectual property (IP), multidisciplinarity teamwork, fast prototyping and product engineering have shortened to a few months an otherwise quite longer idea-to-product route, clearly demonstrating that when scientific and engineering knowledge hold hands great challenges can be successfully faced.

2021

A Performance Analysis of Feature Extraction Algorithms for Acoustic Image-Based Underwater Navigation

Authors
Oliveira, AJ; Ferreira, BM; Cruz, NA;

Publication
JOURNAL OF MARINE SCIENCE AND ENGINEERING

Abstract
In underwater navigation, sonars are useful sensing devices for operation in confined or structured environments, enabling the detection and identification of underwater environmental features through the acquisition of acoustic images. Nonetheless, in these environments, several problems affect their performance, such as background noise and multiple secondary echoes. In recent years, research has been conducted regarding the application of feature extraction algorithms to underwater acoustic images, with the purpose of achieving a robust solution for the detection and matching of environmental features. However, since these algorithms were originally developed for optical image analysis, conclusions in the literature diverge regarding their suitability to acoustic imaging. This article presents a detailed comparison between the SURF (Speeded-Up Robust Features), ORB (Oriented FAST and Rotated BRIEF), BRISK (Binary Robust Invariant Scalable Keypoints), and SURF-Harris algorithms, based on the performance of their feature detection and description procedures, when applied to acoustic data collected by an autonomous underwater vehicle. Several characteristics of the studied algorithms were taken into account, such as feature point distribution, feature detection accuracy, and feature description robustness. A possible adaptation of feature extraction procedures to acoustic imaging is further explored through the implementation of a feature selection module. The performed comparison has also provided evidence that further development of the current feature description methodologies might be required for underwater acoustic image analysis.

2021

A Novel Simulation Platform for Underwater Data Muling Communications Using Autonomous Underwater Vehicles

Authors
Teixeira, FB; Ferreira, BM; Moreira, N; Abreu, N; Villa, M; Loureiro, JP; Cruz, NA; Alves, JC; Ricardo, M; Campos, R;

Publication
Comput.

Abstract
Autonomous Underwater Vehicles (AUVs) are seen as a safe and cost-effective platforms for performing a myriad of underwater missions. These vehicles are equipped with multiple sensors which, combined with their long endurance, can produce large amounts of data, especially when used for video capturing. These data need to be transferred to the surface to be processed and analyzed. When considering deep sea operations, where surfacing before the end of the mission may be unpractical, the communication is limited to low bitrate acoustic communications, which make unfeasible the timely transmission of large amounts of data unfeasible. The usage of AUVs as data mules is an alternative communications solution. Data mules can be used to establish a broadband data link by combining short-range, high bitrate communications (e.g., RF and wireless optical) with a Delay Tolerant Network approach. This paper presents an enhanced version of UDMSim, a novel simulation platform for data muling communications. UDMSim is built upon a new realistic AUV Motion and Localization (AML) simulator and Network Simulator 3 (ns-3). It can simulate the position of the data mules, including localization errors, realistic position control adjustments, the received signal, the realistic throughput adjustments, and connection losses due to the fast SNR change observed underwater. The enhanced version includes a more realistic AML simulator and the antenna radiation patterns to help evaluating the design and relative placement of underwater antennas. The results obtained using UDMSim show a good match with the experimental results achieved using an underwater testbed. UDMSim is made available to the community to support easy and faster evaluation of underwater data muling oriented communications solutions and to enable offline replication of real world experiments.

Supervised
thesis

2021

Information-aware Feature-based Underwater Localization and Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP

2021

Deepwater Intelligent Video Recorder

Author
Luís Páris Couto Venn Fonseca

Institution
UP-FEUP

2021

Efficent Verified MPC

Author
Manuel Luís Magalhães Duarte Correia

Institution
UP-FCUP

2021

Classificação automática de termogramas do pé diabético usando técnicas de machine learning

Author
Pedro Miguel Bento Teixeira

Institution
UP-FEUP

2021

Underwater Localization in Complex Environments

Author
Maria Sara Delgadinho Noronha

Institution
UP-FEUP