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Presentation

Robotics and Autonomous Systems

At CRAS, our mission is to develop innovative robotic solutions for complex environments and multiple operations, including data gathering, inspection, mapping, surveillance, and intervention.

We work in four main areas of research: autonomous navigation; long-term deployments; sensing, mapping, and intervention; multiple platform operations.

Latest News

Ana Pires is the winner of the Science and Technology category of the Women 3.0 Awards

The INESC TEC researcher was part of the group featuring 10 women acknowledged at the Women 3.0 Awards – a recognition that aims to award women considered "agents of change" in the most diverse sectors.

17th January 2024

The prototype of the vehicle of the future is airborne, is autonomous and it features INESC TEC technology

The goal of the FLY.PT mobilising project was to combine land and air mobility. In this project, aimed at revitalising the aeronautical industry, INESC TEC developed a multimodal perception system and an algorithm that meets users' needs.  

05th January 2024

Robotics, biomedical engineering, and education: INESC TEC’s role in the first Portuguese analog mission

A group of seven scientists spent six nights and seven days inside Gruta do Natal (Terceira Island, Azores), replicating the lunar environment. It was the first analog mission carried out in Portugal, and the goal was to turn the Azores into a training site for astronauts from all over the world. They called it the CAMões project (Caving Analog Mission for Ocean, Earth and Space Exploration). INESC TEC, together with the Associação Os Montanheiros, led and organised this project from the beginning; not only because the superior/leader of the mission is a researcher at the institution, Ana Pires, but also because if featured technology from various areas of the Institute, tested and applied to a great mission: to familiarise the younger generations with STEAM (Science, technology, engineering, arts and mathematics).

18th December 2023

INESC TEC researchers excel in critical underwater infrastructure protection challenges in one of the world’s largest robotics exercises

Detecting explosive charges on a submarine cable, or signalling and assessing the status of a submarine, located at a depth of 90 meters – with a crew on board, simulating an emergency situation. These are two examples of the tests carried out by INESC TEC, during REPMUS, the world’s largest testing exercise on Unmanned Marine Systems and other emerging technologies, organised by the Portuguese Navy.

09th November 2023

Portuguese team successfully tests autonomous robots to inspect floating offshore wind farms

The first offshore floating wind farm to be installed off the coast of Europe was the scene of an unprecedented demonstration: two autonomous vehicles were deployed simultaneously for inspection and maintenance operations on an offshore wind farm with floating foundations.

06th November 2023

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Featured Projects

MAR_PreExpTunel4

Proposta para pré inspeção de túnel com recurso a veículo robótico

2024-2024

DiveTrack

Localização e Rastreamento de Mergulhadores

2024-2024

SENTINEL

SpacE operatioNs, moniToring, and mappINg ExpLorer: a smart Orb-system

2024-2024

UWRoboticEMFInspect

Underwater Robotic Offshore EMF Inspection

2024-2025

NauticalSunrise

Survivability assessment, cost reduction pathways and environmental evaluation of offshore installed floating solar energy farms

2023-2027

ILVO2_eBAR

BAR eCollect: automatic collection of eDNA aboard fishing vessels for the characterization of fish stocks

2023-2024

TALOS

roboTics and Artificial intelligence Living labs improving Operations in PV Scenarios

2023-2026

NETTAGPlus

Preventing, avoiding and mitigating environmental impacts of fishing gears and associated marine litter

2023-2026

NMicroARTIC

Nitrogen Microbiome in the Changing Artic

2023-2026

ATE

Alliance for Energy Transition

2023-2025

TRIDENT

Technology based impact assessment tool foR sustaInable, transparent Deep sEa miNing exploraTion and exploitation

2023-2027

MineIO

A Holistic Digital Mine 4.0 Ecosystem

2023-2026

AIRSHIP

AUTONOMOUS FLYING SHIPS FOR INTER-ISLAND AND INLAND WATERS TRANSPORT

2023-2026

AOWINDE

ATLANTIC OFFSHORE WIND ENERGY

2023-2025

AEROGANP

Creación de un eje transfronterizo de investigación y transferencia de conocimiento en el sector aeronáutico y espacial en la Eurorregión Galicia-Norte de Portugal

2023-2026

AECUD_2

Automatic environmental control using eDNA 2

2022-2023

SEAWINGS

Sea/Air Interphasic Wing-in-Ground Effect Autonomous Drones

2022-2026

ASM_research2022

ASM Underwater batteries development

2022-2024

OVERWATCH

Integrated holographic management map for safety and crisis events

2022-2025

NEXUS

Innovation Pact - Digital and Green Transition

2022-2025

NewSpacePortugal

Agenda New Space Portugal

2022-2025

SUMO_PPI_072022

Proposal for the Provision of Support to Marine Operations - PPI July 2022

2022-2022

EDIDPMiricle

MIRICLE (MIne RIsk CLearance for Europe)

2022-2023

Drivolution

Agenda Drivolution

2022-2025

StoneByPortugal

SUISTANABLE StoneByPortugal: Valorização da Pedra Natural para um futuro digital, sustentável e qualificado

2022-2025

FLYPASS

FoiL boat using clean energY for PASSenger transportation

2022-2024

TIMREX

T-Shaped Master Programme for Innovative Mineral Resource Exploration

2022-2024

KRISO_2022

Underwater 3D Environment Perception – VAMOS the case study

2022-2022

FIRELOGUE

Cross-sector dialogue for Wildfire Risk Management

2021-2025

MAGPIE

sMArt Green Ports as Integrated Efficient multimodal hubs

2021-2026

EUSCORES

EUropean - Scalable and Complementary Offshore Renewable Energy Sources

2021-2025

KRISO 2021

Underwater 3D Environment Perception – VAMOS the case study

2021-2021

Connect2Oceans

Connecting Atlantic and Arctic Oceans to Decipher Climate Change Impact on Plankton Microbiome Functions

2021-2024

AECUD

Automatic environmental control using eDNA

2021-2021

PORT XXI

Space Enabled Sustainable Port Services

2020-2022

NoduleMiner6k

Conceptual design of a Polymetallic Nodule Miner

2020-2021

SHIELD

Safeguard Heritage in Endangered Looted Districts

2020-2023

KRISO 2020

Underwater 3D Environment Perception, Awareness, Reasoning for CPOS (Cyber-Physical Operation System) of Underwater Robots

2020-2020

K2D

Knowledge and Data from the Deep to Space

2020-2023

REV@CONSTRUCTION

Digital construction revolution

2020-2023

FLY_PT

Mobilizar a indústria aeronáutica nacional para a disrupção no transporte aéreo urbano do futuro

2020-2023

NEWSAT

Development of a compact integrated sensor and satellite for earth observation

2020-2023

ATLANTIS

The Atlantic Testing Platform for Maritime Robotics: New Frontiers for Inspection and Maintenance of Offshore Energy Infrastructures

2020-2024

UNEXUP

UNEXMIN Upscaling

2020-2022

QuALTOS

Quality Assurance in Long Term Observation Systems

2020-2022

Sail2020

Space-Atmosphere-Ocean Interactions in the marine boundary Layer

2020-2020

inSITE

inSITE. Insitu ore grading system using LIBS in harsh environments

2020-2022

DEEPFIELD

DeepField- Deep Learning in Field Robotics: from conceptualization towards implementation

2019-2023

ESAPlastics

De-risk assessment: spectrometer for marine litter

2019-2021

SPRING

Strategic planning for water resources and implementation of novel biotechnical treatment solutions and good practices

2019-2024

SensiTermo_1

Estudo técnico de tecnologias e componentes eletrónicos para a monitorização da passagem de água em termoacumuladores de forma não intrusiva

2019-2019

SantoAntonio

ROV de inspeção e apoio à limpeza para Santo António Energia

2019-2021

SVManagement

Apoio à constituição de uma equipa de investigação e desenvolvimeto da Clínica Saúde Viável

2019-2019

MetroRec

Avaliação do sistema gravação vídeo do Metro do Porto

2019-2019

Nettag

Tagging fishing gears and enhancing on board best-practices to promote waste free fisheries

2019-2021

Mine_Heritage

Historical Mining – tracing and learning from ancient materials and mining technology

2019-2021

NESSIE

moNitoring offshorE StructureS with robotIc systems intEgration

2019-2023

Prince

Preparedness Response for CBRNE INCidEnts

2019-2022

GROW

Long-range broadband underwater wireless communications

2018-2021

DIIUS

Distributed perceptIon for inspectIon of aqUatic Structures

2018-2022

ENDURANCE

Underwater wireless energy and communications enabling long-term deep-sea presence

2018-2020

HiperSea

Sistema Hiperbárico para Recolha e Manutenção de Organismos do Mar Profundo

2018-2022

BIOREM

Bioremediation of hydrocarbon pollutants by autochthonous microorganisms in aquatic environment

2018-2021

INTENDU

Integrated Technologies Longterm Deployment of Robotic Underwater platforms

2018-2021

FEEDFIRST

Desenvolvimento de uma nova tecnologia para cultivo de larvas de peixes à primeira alimentação

2018-2021

PROTOATLANTIC

Development and validation of a program for the prototyping and exploitation of innovative ideas

2017-2023

ROSM

Sistema robótico de mitigação de derrame de crude

2017-2019

AutoMon

MMonitorização automatizada de Recursos Hídricos

2017-2021

TEC4Sea

Modular Platform for Research, Test and Validation of Technologies supporting a Sustainable Blue Economy

2017-2022

EMSO-PT

Observatório Europeu Multidisciplinar do Fundo do Mar e Coluna de Água - Portugal

2017-2023

SpilLess

First line response to oil spills based on native microorganisms cooperation (SpilLess)

2017-2019

SIDENAV

Smart infrastructure for deep sea navigation

2016-2018

RAWFIE

Road-, Air- and Water-based Future Internet Experimentation

2016-2019

HAIFA

Buoys for marine equipment

2016-2017

MyTag-CRAS

Integrating natural and artificial tags to reconstruct fish migrations and ontogenetic niche shifts

2016-2019

EDA-SAVEWATE-CRAS

System of Autonomous Vehicles for Water Environments for Defense

2016-2018

Fmanagement

Fmanagement

2016-2017

DeepFloat

Sistema de variação de flutuação para aplicações submarinas

2016-2018

UNEXMIN-CRAS

Autonomous Underwater Explorer for Flooded Mines

2016-2019

CORAL-SENSORS

CORAL – Sustainable Ocean Exploitation: Tools and Sensors

2016-2018

CORAL-TOOLS

CORAL – Sustainable Ocean Exploitation: Tools and Sensors

2016-2018

STRONGMAR-CRAS

STRengthening MARritime Technology Research Center

2016-2018

EMSODEV

EMSO implementation and operation: DEVelopment of instrument module

2015-2018

MarineEye

MarinEye - A prototype for multitrophic oceanic monitoring

2015-2017

BLUECOM+

Connecting Humans and Systems at Remote Ocean Areas using Cost-effective Broadband Communications

2015-2017

ENDURE

Enabling Long-Term Deployments of Underwater Robotic Platforms in Remote Oceanic Locations

2015-2017

Demo_Drone

Demonstração de capacidades de utilização de Drones para inspeção detalhada de ativos de rede

2015-2018

CINMarS

Combining Space and Maritime NetWorks

2015-2017

VAMOS

Viable Alternative Mine Operating System

2015-2019

SUNNY

Smart UNmanned aerial vehicle sensor Network for detection of border crossing and illegal entrY

2014-2018

Evologics-CRAS

Real Time LBL Data Fusion for Acoustic Modems

2013-2019

ICARUS-CRAS

Integrated Components for Assisted Rescue and Unmanned Search operations

2012-2016

SUB.2-CRAS

Propelled underwater vehicle carrying energy, electronic and computing systems on board, capable of operating autonomously without being connected to the operator

2012-2015

Team
001

Laboratories

Robotics and Autonomous Systems Laboratory

Publications

CRAS Publications

View all Publications

2024

Probabilistic Positioning of a Mooring Cable in Sonar Images for In-Situ Calibration of Marine Sensors

Authors
Oliveira A.J.; Ferreira B.M.; Cruz N.A.; Diamant R.;

Publication
IEEE Transactions on Mobile Computing

Abstract
The calibration of sensors stationed along a cable in marine observatories is a time-consuming and expensive operation that involves taking the mooring out of the water periodically. In this paper, we present a method that allows an underwater vehicle to approach a mooring, in order to take reference measurements along the cable for in-situ sensor calibration. We use the vehicle's Mechanically Scanned Imaging Sonar (MSIS) to identify the cable's reflection within the sonar image. After pre-processing the image to remove noise, enhance contour lines, and perform smoothing, we employ three detection steps: 1) selection of regions of interest that fit the cable's reflection pattern, 2) template matching, and 3) a track-before-detect scheme that utilized the vehicle's motion. The later involves building a lattice of template matching responses for a sequence of sonar images, and using the Viterbi algorithm to find the most probable sequence of cable locations that fits the maximum speed assumed for the surveying vessel. Performance is explored in pool and sea trials, and involves an MSIS onboard an underwater vehicle scanning its surrounding to identify a steel-core cable. The results show a sub-meter accuracy in the multi-reverberant pool environment and in the sea trial. For reproducibility, we share our implementation code.

2024

Fusing heterogeneous tri-dimensional information for reconstructing submerged structures in harsh sub-sea environments

Authors
Leite, PN; Pinto, AM;

Publication
INFORMATION FUSION

Abstract
Exploiting stronger winds at offshore farms leads to a cyclical need for maintenance due to the harsh maritime conditions. While autonomous vehicles are the prone solution for O&M procedures, sub-sea phenomena induce severe data degradation that hinders the vessel's 3D perception. This article demonstrates a hybrid underwater imaging system that is capable of retrieving tri-dimensional information: dense and textured Photogrammetric Stereo (PS) point clouds and multiple accurate sets of points through Light Stripe Ranging (LSR), that are combined into a single dense and accurate representation. Two novel fusion algorithms are introduced in this manuscript. A Joint Masked Regression (JMR) methodology propagates sparse LSR information towards the PS point cloud, exploiting homogeneous regions around each beam projection. Regression curves then correlate depth readings from both inputs to correct the stereo-based information. On the other hand, the learning-based solution (RHEA) follows an early-fusion approach where features are conjointly learned from a coupled representation of both 3D inputs. A synthetic-to-real training scheme is employed to bypass domain-adaptation stages, enabling direct deployment in underwater contexts. Evaluation is conducted through extensive trials in simulation, controlled underwater environments, and within a real application at the ATLANTIS Coastal Testbed. Both methods estimate improved output point clouds, with RHEA achieving an average RMSE of 0.0097 m -a 52.45% improvement when compared to the PS input. Performance with real underwater information proves that RHEA is robust in dealing with degraded input information; JMR is more affected by missing information, excelling when the LSR data provides a complete representation of the scenario, and struggling otherwise.

2024

Smart Stress Relief – An EPS@ISEP 2022 Project

Authors
Cifuentes, GR; Camps, J; do Nascimento, JL; Bode, JA; Duarte, J; Malheiro, B; Ribeiro, C; Justo, J; Silva, F; Ferreira, P; Guedes, P;

Publication
Lecture Notes in Networks and Systems

Abstract
Mild is a smart stress relief solution created by DSTRS, an European Project Semester student team enrolled at the Instituto Superior de Engenharia do Porto in the spring of 2022. This paper details the research performed, concerning ethics, marketing, sustainability and state-of-the-art, the ideas, concept and design pursued, and the prototype assembled and tested by DSTRS. The designed kit comprises a bracelet, pair of earphones with case, and a mobile app. The bracelet reads the user heart beat and temperature to automatically detect early stress signs. The case and mobile app command the earphones to play sounds based on the user readings or on user demand. Moreover, the case includes a tactile distractor, a scent diffuser and vibrates. This innovative multi-sensory output, combining auditory, olfactory, tactile and vestibular stimulus, intends to sooth the user. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

2024

Explainable Classification of Wiki Streams

Authors
García Méndez, S; Leal, F; de Arriba Pérez, F; Malheiro, B; Burguillo Rial, JC;

Publication
Lecture Notes in Networks and Systems

Abstract
Web 2.0 platforms, like wikis and social networks, rely on crowdsourced data and, as such, are prone to data manipulation by ill-intended contributors. This research proposes the transparent identification of wiki manipulators through the classification of contributors as benevolent or malevolent humans or bots, together with the explanation of the attributed class labels. The system comprises: (i) stream-based data pre-processing; (ii) incremental profiling; and (iii) online classification, evaluation and explanation. Particularly, the system profiles contributors and contributions by combining features directly collected with content- and side-based engineered features. The experimental results obtained with a real data set collected from Wikivoyage – a popular travel wiki – attained a 98.52% classification accuracy and 91.34% macro F-measure. In the end, this work seeks to address data reliability to prevent information detrimental and manipulation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

2024

Balancing Plug-In for Stream-Based Classification

Authors
de Arriba Pérez, F; García Méndez, S; Leal, F; Malheiro, B; Burguillo Rial, JC;

Publication
Lecture Notes in Networks and Systems

Abstract
The latest technological advances drive the emergence of countless real-time data streams fed by users, sensors, and devices. These data sources can be mined with the help of predictive and classification techniques to support decision-making in fields like e-commerce, industry or health. In particular, stream-based classification is widely used to categorise incoming samples on the fly. However, the distribution of samples per class is often imbalanced, affecting the performance and fairness of machine learning models. To overcome this drawback, this paper proposes Bplug, a balancing plug-in for stream-based classification, to minimise the bias introduced by data imbalance. First, the plug-in determines the class imbalance degree and then synthesises data statistically through non-parametric kernel density estimation. The experiments, performed with real data from Wikivoyage and Metro of Porto, show that Bplug maintains inter-feature correlation and improves classification accuracy. Moreover, it works both online and offline. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Facts & Figures

7Proceedings in indexed conferences

2020

40Researchers

2016

1Book Chapters

2020

Contacts