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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
Networked Intelligent Systems

INESC TEC tested one of the most advanced underwater robots in the world

The testing of the UX-1Neo autonomous robot, developed to explore flooded underground mines, took place on May 27, at the old Urgeiriça uranium mine (Nelas, Viseu). These were the first tests of the robot developed by INESC TEC’s Centre for Robotics and Autonomous Systems (CRAS), within the scope of the European project UNEXUP.

28th May 2021

Networked Intelligent Systems

INESC TEC leads project that aims to "clean up" the Azores ports

INESC TEC, through its Centre for Robotics and Autonomous Systems (CRAS) is the leader of the PORT XXI - Space Enabled Sustainable Port Service project, which aims to develop and implement monitoring and environmental management solutions, in order to improve the management of complex activities and achieve zero pollution in the ports of Azores.

04th March 2021

Networked Intelligent Systems

INESC TEC project for the development of digital technologies to safeguard archaeological heritage

In November, INESC TEC launched the SHIELD project, focused on adapting an Unmanned Aerial System (UAS) against looting activities at archaeological sites.

26th November 2020

Networked Intelligent Systems

INESC TEC supports ABB Marine & Ports in the development of an optimisation tool for the O&M in offshore wind farms

INESC TEC, as the coordinator of the European project ATLANTIS – The Atlantic Testing Platform for Maritime Robotics: New Frontiers for Inspection and Maintenance of Offshore Energy Infrastructures, is supporting ABB Marine & Ports for the development of an optimisation software that aims to improve the inspection and maintenance of offshore wind farms, in order to reduce costs and increase the efficiency, safety and sustainability of these structures.

26th November 2020

Networked Intelligent Systems

INESC TEC tests technology to detect marine litter remotely

The testing phase of the Spectrometer for Marine Litter project, led by the Centre for Robotics and Autonomous Systems (CRAS), took place between September 16 and 25, in Faial (Azores). The objective was to test the potential of using hyperspectral sensors for the remote detection of marine litter in coastal areas and shallow waters.

20th October 2020

Interest Topics
062

Featured Projects

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

PORT XXI

PORT XXI – Space Enabled Sustainable Port Services

2020-2021

NoduleMiner6k

NoduleMiner6k

2020-2021

SHIELD

Safeguard Heritage in Endangered Looted Districts

2020-2022

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

inSITE

inSITE. Insitu ore grading system using LIBS in harsh environments

2020-2022

ATLANTIS

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

2020-2022

UNEXUP

UNEXUP. UNEXMIN Upscaling

2020-2022

QuALTOS

Quality Assurance in Long Term Observation Systems

2020-2021

Sail2020

Space-Atmosphere-Ocean Interactions in the marine boundary Layer

2020-2020

RHAQ

Contratação de Recursos Humanos Altamente Qualificados

2020-2023

DEEPFIELD

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

2019-2022

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

2019-2023

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

2019-2021

Prince

Preparedness Response for CBRNE INCidEnts

2019-2021

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

2018-2021

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

2017-2021

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

2017-2021

EMSO-PT

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

2017-2021

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

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

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

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

Classification and Recommendation With Data Streams

Authors
Veloso, B; Gama, J; Malheiro, B;

Publication
Encyclopedia of Information Science and Technology, Fifth Edition - Advances in Information Quality and Management

Abstract
Nowadays, with the exponential growth of data stream sources (e.g., Internet of Things [IoT], social networks, crowdsourcing platforms, and personal mobile devices), data stream processing has become indispensable for online classification, recommendation, and evaluation. Its main goal is to maintain dynamic models updated, holding the captured patterns, to make accurate predictions. The foundations of data streams algorithms are incremental processing, in order to reduce the computational resources required to process large quantities of data, and relevance model updating. This article addresses data stream knowledge processing, covering classification, recommendation, and evaluation; describing existing algorithms/techniques; and identifying open challenges.

2021

The MopBot Cleaning Robot – An EPS@ISEP 2020 Project

Authors
Tuluc, C; Verberne, F; Lasota, S; de Almeida, T; Malheiro, B; Justo, J; Ribeiro, C; Silva, MF; Ferreira, P; Guedes, P;

Publication
Educating Engineers for Future Industrial Revolutions - Advances in Intelligent Systems and Computing

Abstract

Supervised Theses

2020

Sistema de reconstrução 3D com LiDAR e câmara de espetro visível para veículo autónomo aéreo

Author
Pedro André Peixoto Fonseca de Castro e silva

Institution
IPP-ISEP

2020

Modelação e Simulação de um Veleiro Terrestre com Vela Asa

Author
VÍTOR DANIEL VELOSO TINOCO

Institution
IPP-ISEP

2020

Multi-agent Reinforcement Learning for Distributed Perception Systems in Maritime Environments

Author
Maria Inês Rodrigues Pereira

Institution
INESCTEC

2020

Sistema Autónomo de Aquisição de Imagens de Alta Resolução de Plâncton

Author
JOÃO FILIPE AMORIM RESENDE

Institution
IPP-ISEP

2020

Object Detection and Tracking for ASV

Author
DIMPI RAJUBHAI PATEL

Institution
IPP-ISEP

Facts & Figures

15Senior Researchers

2016

11Academic Staff

2020

40Researchers

2016

Contacts