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About

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/

Interest
Topics
Details

Details

  • Name

    Nuno Cruz
  • Role

    Centre Coordinator
  • Since

    01st June 2009
023
Publications

2023

Model Identification and Control of a Buoyancy Change Device

Authors
Carneiro, JF; Pinto, JB; de Almeida, FG; Cruz, NA;

Publication
ACTUATORS

Abstract
There are several compelling reasons for exploring the ocean, for instance, the potential for accessing valuable resources, such as energy and minerals; establishing sovereignty; and addressing environmental issues. As a result, the scientific community has increasingly focused on the use of autonomous underwater vehicles (AUVs) for ocean exploration. Recent research has demonstrated that buoyancy change modules can greatly enhance the energy efficiency of these vehicles. However, the literature is scarce regarding the dynamic models of the vertical motion of buoyancy change modules. It is therefore difficult to develop adequate depth controllers, as this is a very complex task to perform in situ. The focus of this paper is to develop simplified linear models for a buoyancy change module that was previously designed by the authors. These models are experimentally identified and used to fine-tune depth controllers. Experimental results demonstrate that the controllers perform well, achieving a virtual zero steady-state error with satisfactory dynamic characteristics.

2023

Estimation of Sediments in Underwater Wall Corners using a Mechanical Scanning Sonar

Authors
Goncalves, CF; Cruz, NA; Ferreira, BM;

Publication
2023 IEEE International Symposium on Underwater Technology, UT 2023

Abstract
This paper describes a robotic system to detect and estimate the volume of sediments in underwater wall corners, in scenarios with zero visibility. All detection and positioning is based on data from a scanning sonar. The main idea is to scan the walls and the bottom of the structure to detect the corner, and then use data obtained in the direction of the corner to estimate the presence of sediment accumulation and its volume. Our approach implements an image segmentation to extract range from the surfaces of interest. The resulting data is then employed for relative localization and estimate of the sediment accumulation. The paper provides information about the methodologies developed and data from practical experiments. © 2023 IEEE.

2023

Single Receiver Underwater Localization of an Unsynchronized Periodic Acoustic Beacon Using Synthetic Baseline

Authors
Ferreira, BM; Graça, PA; Alves, JC; Cruz, NA;

Publication
IEEE JOURNAL OF OCEANIC ENGINEERING

Abstract
This article addresses the 3-D localization of a stand-alone acoustic beacon based on the Principle of Synthetic Baseline using a single receiver on board a surface vehicle. The process only uses the passive reception of an acoustic signal with no explicit synchronization, interaction, or communication with the acoustic beacon. The localization process exploits the transmission of periodic signals without synchronization to a known time reference to estimate the time-of-arrival (ToA) with respect to an absolute time basis provided by the global navigation satellite system (GNSS). We present the development of the acoustic signal acquisition system, the signal processing algorithms, the data processing of times-of-arrival, and an estimator that uses times-of-arrival and the coordinates where they have been collected to obtain the 3-D position of the acoustic beacon. The proposed approach was validated in a real field application on a search for an underwater glider lost in September 2021 near the Portuguese coast.

2023

Estimation of Sediments in Underwater Wall Corners using a Mechanical Scanning Sonar

Authors
Goncalves, CF; Cruz, NA; Ferreira, BM;

Publication
2023 IEEE International Symposium on Underwater Technology, UT 2023

Abstract
This paper describes a robotic system to detect and estimate the volume of sediments in underwater wall corners, in scenarios with zero visibility. All detection and positioning is based on data from a scanning sonar. The main idea is to scan the walls and the bottom of the structure to detect the corner, and then use data obtained in the direction of the corner to estimate the presence of sediment accumulation and its volume. Our approach implements an image segmentation to extract range from the surfaces of interest. The resulting data is then employed for relative localization and estimate of the sediment accumulation. The paper provides information about the methodologies developed and data from practical experiments. © 2023 IEEE.

2023

Estimation of Sediments in Underwater Wall Corners using a Mechanical Scanning Sonar

Authors
Goncalves, CF; Cruz, NA; Ferreira, BM;

Publication
2023 IEEE UNDERWATER TECHNOLOGY, UT

Abstract
This paper describes a robotic system to detect and estimate the volume of sediments in underwater wall corners, in scenarios with zero visibility. All detection and positioning is based on data from a scanning sonar. The main idea is to scan the walls and the bottom of the structure to detect the corner, and then use data obtained in the direction of the corner to estimate the presence of sediment accumulation and its volume. Our approach implements an image segmentation to extract range from the surfaces of interest. The resulting data is then employed for relative localization and estimate of the sediment accumulation. The paper provides information about the methodologies developed and data from practical experiments.

Supervised
thesis

2022

Autonomous Robotic Bathymetric Mapping

Author
João Burmester Campos

Institution
UP-FEUP

2022

Information-aware Feature-based Underwater Localization and Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP

2021

Underwater picking

Author
Samuel Aguiar Pereira

Institution
UP-FEUP

2021

Information-aware Feature-based Underwater Localization and Planning

Author
António José Ventura de Oliveira

Institution
UP-FEUP

2021

Experimental evaluation of segmentation algorithms for corner detection in sonar images

Author
Pedro Miguel Linhares Oliveira

Institution
UP-FEUP