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Apresentação

Centro de Robótica Industrial e Sistemas Inteligentes

No CRIIS trabalhamos em estreita colaboração com empresas, outros Institutos e Universidades, seguindo o lema da Investigação e Desenvolvimento até à Inovação, Design, Prototipagem e Implementação.

O Centro aborda as seguintes áreas de investigação principais: Navegação e Localização de Robôs Móveis, Sensores Inteligentes e Controlo de Sistemas Dinâmicos, Visão Industrial 2D/3D e Deteção Avançada, Manipuladores Móveis, Estruturas Especiais e Arquiteturas para Robôs, Interfaces de Robô-Humano e Realidade Aumentada, Robótica Industrial e Robôs Colaborativos do Futuro, Integração Vertical, IoT e Indústria 4.0.

Últimas Notícias
Indústria e Inovação

INESC TEC desenvolve robô pintor que colabora com humanos

Os investigadores do Centro de Robótica Industrial e Sistemas Inteligentes (CRIIS) do INESC TEC, juntamente com a empresa portuguesa TALUS, desenvolveram um robô pintor que colabora com humanos.

31 outubro 2019

Tecnologias do INESC TEC marcam presença na mostra TECH@Portugal

Quatro demonstradores e um laboratório colaborativo. Foi desta forma que o INESC TEC marcou presença na mostra tecnológica promovida pela Agência Nacional de Inovação (ANI), que decorreu no dia 4 de julho, no Centro de Congressos da Alfândega do Porto.

22 julho 2019

Indústria e Inovação

Conferência internacional sobre inovação promovida pela COTEC com participação do INESC TEC

O INESC TEC participou, no dia 8 de julho, na 16th COTEC Innovation Summit, subordinada ao tema "Leading 4.0 – Highway to manufacture value with people and intelligent machines”. 

19 julho 2019

Indústria e Inovação

Robótica industrial apresentada a estudantes em Vila Real

Luís Santos, Pranjali Shinde e Jorge Mendes, colaboradores do Centro de Robótica Industrial e Sistemas Inteligentes (CRIIS) do INESC TEC, participaram, no dia 10 de maio, num evento destinado a estudantes do secundário, com o objetivo de dar a conhecer o trabalho da universidade, nomeadamente na aplicação de tecnologia a contextos reais.

18 junho 2019

INESC TEC estreia-se na 360 Tech Industry

No âmbito da abordagem ao setor da Indústria, o INESC TEC esteve presente na primeira edição da 360 TECH INDUSTRY – Feira Internacional da Indústria 4.0, Robótica, Automação e Compósitos, que decorreu de 16 a 18 de maio na Exponor, no Porto.

18 junho 2019

Tópicos de interesse
050

Projetos Selecionados

CrossLOG

Concretização de sistema físico e software para paletização mista automática em centros logísticos cross-docking para cadeias de valor responsive demand-driven

2019-2022

DEMETER

Building an Interoperable, Data-Driven, Innovative and Sustainable European Agri-Food Sector

2019-2023

T4CDTKC

Training 4 Cotec, Digital Transformation Knowledge Challenge - Elaboração de Programa de Formação “CONHECER E COMPREENDER O DESAFIO DAS TECNOLOGIAS DE TRANSFORMAÇÃO DIGITAL”

2019-2020

Jales

TRABALHOS DE INTERFEROMETRIA SAR NA ÁREA MINEIRA DE JALES

2019-2019

AgRoBoFood

agROBOfood: Business-Oriented Support to the European Robotics and Agri-food Sector, towards a network of Digital Innovation Hubs in Robotics

2019-2023

Rosin

Active managed Buildings with Energy performaNce Contracting

2019-2019

Smart-Fertilizers

SMART FERTELIZERS - Espalhadores e Cisternas inteligentes

2019-2020

SAFE

Sistema de Monitorização e Alerta Florestal

2019-2020

ROBOTICA2019

ROBOTICA2019

2019-2019

PBA

Unified Framework for Mobile Robots

2018-2019

HORSE

Collaborative Robotics for Industrial Coating Cells

2018-2019

Refinacao4.0

Serviços de consultoria especializada para desenvolvimento e operacionalização de provas de conceito

2018-2020

MetBots

Robots para metabolómica utilizando inteligência artificial com autoaprendizagem em agricultura de precisão.

2018-2020

SAFER

Verificação de segurança para software robótico

2018-2021

COBOTIS

Interação homem-robô para a robótica colaborativa

2018-2021

COATING4.0

ANALYSIS AND DESIGN OF AN INNOVATIVE REMOTE PROCESS MANAGEMENT AND MONITORING SOLUTION (4.0)

2018-2019

FED

Ferradura, programação intuitiva para aplicações de soldadura robotizada

2018-2019

DIVA

Boosting innovative DIgitech Value chains for Agrofood, forestry and environment

2018-2021

FDControlo

Importância dos hospedeiros alternativos (plantas, insetos, vitis abandonada) na dispersão da doença da flavescência dourada (FD) da vinhda e das populações de scapholdeus titanus nas sub-regiões vitivinículas do Cávado e do Lima

2018-2021

DroneTool

Service to develop a prototype of a drone end-effector for leaf harvesting

2017-2019

Fasten

Flexible and Autonomous Manufacturing Systems for Custom-Designed Products

2017-2020

FAMEST

Calçado e tecnologias avançadas de materiais, equipamentos e software

2017-2020

PRODUTECH_SIF

Soluções para a Indústria de Futuro

2017-2020

Water4Ever

Optimização na utilização da água na agricultura para preservação do solo e recursos hídricos

2017-2020

RIDDIG

Fábrica Digital

2017-2019

SistemaDPA

Sistema DPA para Espalhador de Estrume (sem ISOBUS) e Análise Química (NIR sensor) para Cisterna em Ambiente ISOBUS.

2017-2019

MANUFACTUR4.0

Desenvolvimento e implementação de tecnologias inteligentes e inovadoras nos setores industriais naval e metalomecânico

2017-2019

AGRINUPES

Integrated monitoring and control of water, nutrients and plant protection products towards a sustainable agricultural sector

2017-2020

Palcus

Sistema de Controlo de Máquinas Cénicas

2017-2017

ROMOVI

ROMOVI: Robô Modular e cooperativo para Vinhas de encosta

2017-2019

ScalABLE4.0

Scalable automation for flexible production systems

2017-2020

BIOTECFOR

Bionegócios e Tecnologia para a valorização eficiente dos recursos florestais endógenos no Norte de Portugal e Galiza

2017-2019

UnVirtual

Serviço de engenharia e desenvolvimento de robôs para jogo Unvirtual

2017-2018

GOTECFOR

Tecnologia para a mobilização e aproveitamento de Biomassa Florestal na agroindústria

2017-2020

DM4Manufacturing

DM4Manufacturing: Aligning Manufacturing Decision Making with Advanced Manufacturing Technologies

2016-2020

SmartFarming

Ferramenta avançada para operacionalização da agricultura de precisão

2016-2018

AdaptPack

Desenvolvimento de sistemas robóticos de paletização adaptativos e modulares de elevada flexibilidade

2016-2019

ATM

Advanced tools management

2016-2018

Inspectum

Sistema de Visão Artificial para Inspeção de Marcações Típicas em Pneus

2016-2017

TRiHo

RDH - Robot de Distribuição Hospitalar

2016-2019

PrecisionCork

PRECISIONcork - Medida e Controlo em Linha de Parâmetros Chave de Processo e de Qualidade de Produto

2016-2018

ColRobot

Collaborative Robotics for Assembly and Kitting in Smart Manufacturing

2016-2019

TEXTILPRINT

Desenvolvimento e programação de um novo sensor de resina, programação de cabeças de impressão, apoio ao desenvolvimento de software de monitorização e diagnóstico remoto a instalar nas máquinas de impressão textil

2016-2018

CoopWeld

Robótica colaborativa para soldadura de componentes em construção metálica

2015-2017

iMAN

TEC4Growth - RL iMAN - Intelligence for advanced Manufacturing systems

2015-2019

Submarino_Whale

Elaboração do projeto técnico de um dispositivo de controlo pneumático para equilíbrio hidrostático de um submersível

2015-2015

AutoClassII

Automatic Classification and Quality Control for Car Tires

2015-2018

FOCUS

Avanços nos sistemas de Automação e Controlo Florestal na Europa

2014-2016

CLARISSA

The European Robotics Initiative for Strengthening the Competitiveness of SMEs in Manufacturing by integrating aspects of cognitive systems

2014-2016

STAMINA

Robótica Sustentável e Fiável para a Manipulação de Peças em Ambientes Fabris

2013-2017

Equipa
003

Laboratórios

Laboratório de Robótica Industrial e Automação

Laboratório de Robótica Móvel e Logística Interna

Laboratório de Robótica na Agricultura e na Floresta

Publicações

CRIIS Publicações

Ler todas as publicações

2019

Collaborative Welding System using BIM for Robotic Reprogramming and Spatial Augmented Reality

Autores
Tavares, P; Costa, CM; Rocha, L; Malaca, P; Costa, P; Moreira, AP; Sousa, A; Veiga, G;

Publicação
Automation in Construction

Abstract
The optimization of the information flow from the initial design and through the several production stages plays a critical role in ensuring product quality while also reducing the manufacturing costs. As such, in this article we present a cooperative welding cell for structural steel fabrication that is capable of leveraging the Building Information Modeling (BIM) standards to automatically orchestrate the necessary tasks to be allocated to a human operator and a welding robot moving on a linear track. We propose a spatial augmented reality system that projects alignment information into the environment for helping the operator tack weld the beam attachments that will be later on seam welded by the industrial robot. This way we ensure maximum flexibility during the beam assembly stage while also improving the overall productivity and product quality since the operator no longer needs to rely on error prone measurement procedures and he receives his tasks through an immersive interface, relieving him from the burden of analyzing complex manufacturing design specifications. Moreover, no expert robotics knowledge is required to operate our welding cell because all the necessary information is extracted from the Industry Foundation Classes (IFC), namely the CAD models and welding sections, allowing our 3D beam perception systems to correct placement errors or beam bending, which coupled with our motion planning and welding pose optimization system ensures that the robot performs its tasks without collisions and as efficiently as possible while maximizing the welding quality. © 2019 Elsevier B.V.

2019

Modeling of video projectors in OpenGL for implementing a spatial augmented reality teaching system for assembly operations

Autores
Costal, CM; Veiga, G; Sousa, A; Rocha, L; Sousa, AA; Rodrigues, R; Thomas, U;

Publicação
19th IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2019

Abstract
Teaching complex assembly and maintenance skills to human operators usually requires extensive reading and the help of tutors. In order to reduce the training period and avoid the need for human supervision, an immersive teaching system using spatial augmented reality was developed for guiding inexperienced operators. The system provides textual and video instructions for each task while also allowing the operator to navigate between the teaching steps and control the video playback using a bare hands natural interaction interface that is projected into the workspace. Moreover, for helping the operator during the final validation and inspection phase, the system projects the expected 3D outline of the final product. The proposed teaching system was tested with the assembly of a starter motor and proved to be more intuitive than reading the traditional user manuals. This proof of concept use case served to validate the fundamental technologies and approaches that were proposed to achieve an intuitive and accurate augmented reality teaching application. Among the main challenges were the proper modeling and calibration of the sensing and projection hardware along with the 6 DoF pose estimation of objects for achieving precise overlap between the 3D rendered content and the physical world. On the other hand, the conceptualization of the information flow and how it can be conveyed on-demand to the operator was also of critical importance for ensuring a smooth and intuitive experience for the operator. © 2019 IEEE.

2019

Monocular Visual Odometry Benchmarking and Turn Performance Optimization

Autores
Aguiar, A; Sousa, A; dos Santos, FN; Oliveira, M;

Publicação
19th IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2019

Abstract
Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System. In this context, a reliable localization system requires an accurate and redundant information to Global Navigation Satellite System and wheel odometry based system. To pursue this goal we benchmark 3 well known Visual Odometry methods with 2 datasets. Two of these are feature-based Visual Odometry algorithms: Libviso2 and SVO 2.0. The third is an appearance-based Visual Odometry algorithm called DSO. In monocular Visual Odometry, two main problems appear: pure rotations and scale estimation. In this paper, we focus on the first issue. To do so, we propose a Kalman Filter to fuse a single gyroscope with the output pose of monocular Visual Odometry, while estimating gyroscope's bias continuously. In this approach we propose a non-linear noise variation that ensures that bias estimation is not affected by Visual Odometry resultant rotations. We compare and discuss the three unchanged methods and the three methods with the proposed additional Kalman Filter. For tests, two public datasets are used: the Kitti dataset and another built in-house. Results show that our additional Kalman Filter highly improves Visual Odometry performance in rotation movements. © 2019 IEEE.

2019

Modeling of video projectors in OpenGL for implementing a spatial augmented reality teaching system for assembly operations

Autores
Costa, CM; Veiga, G; Sousa, A; Rocha, L; Augusto Sousa, AA; Rodrigues, R; Thomas, U;

Publicação
2019 19TH IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2019)

Abstract
Teaching complex assembly and maintenance skills to human operators usually requires extensive reading and the help of tutors. In order to reduce the training period and avoid the need for human supervision, an immersive teaching system using spatial augmented reality was developed for guiding inexperienced operators. The system provides textual and video instructions for each task while also allowing the operator to navigate between the teaching steps and control the video playback using a bare hands natural interaction interface that is projected into the workspace. Moreover, for helping the operator during the final validation and inspection phase, the system projects the expected 3D outline of the final product. The proposed teaching system was tested with the assembly of a starter motor and proved to be more intuitive than reading the traditional user manuals. This proof of concept use case served to validate the fundamental technologies and approaches that were proposed to achieve an intuitive and accurate augmented reality teaching application. Among the main challenges were the proper modeling and calibration of the sensing and projection hardware along with the 6 DoF pose estimation of objects for achieving precise overlap between the 3D rendered content and the physical world. On the other hand, the conceptualization of the information flow and how it can be conveyed on-demand to the operator was also of critical importance for ensuring a smooth and intuitive experience for the operator.

2019

Learning low level skills from scratch for humanoid robot soccer using deep reinforcement learning

Autores
Abreu, M; Lau, N; Sousa, A; Reis, LP;

Publicação
19th IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2019

Abstract
Reinforcement learning algorithms are now more appealing than ever. Recent approaches bring power and tuning simplicity to the everyday work machine. The possibilities are endless, and the idea of automating learning without domain knowledge is quite tempting for many researchers. However, in competitive environments such as the RoboCup 3D Soccer Simulation League, there is a lot to be done regarding humanlike behaviors. Current teams use many mechanical movements to perform basic skills, such as running and dribbling the ball. This paper aims to use the PPO algorithm to optimize those skills, achieving natural gaits without sacrificing performance. We use Simspark to simulate a NAO humanoid robot, using visual and body sensors to control its actuators. Based on our results, we propose an indirect control approach and detailed parameter setups to obtain natural running and dribbling behaviors. The obtained performance is in some cases comparable or better than the top RoboCup teams. However, some skills are not ready to be applied in competitive environments yet, due to instability. This work contributes towards the improvement of RoboCup and some related technical challenges. © 2019 IEEE.

Teses Orientadas

2018

Produção de lúpulo nacional: uma estratégia para a sustentabilidade

Autor
Sandra Cristina Pereira Afonso

Instituição
UP-FCUP

2018

Monitorização da dinâmica de vegetação dos sistemas de Agricultura Itinerante da região sul de Moçambique através de técnicas de detecção remota

Autor
Sosdito Estevao Mananze

Instituição
UP-FCUP

2018

Design of a low power transmitter for UWB applications

Autor
Iman Kianpour

Instituição
UP-FEUP

2018

Development of robotic manipulators for scalable production lines

Autor
Paulo Diogo Carvalho Ribeiro

Instituição
UP-FEUP

2018

Ferramenta para Desenvolvimento de Inteligência em Jogos Simulados em ambiente Simtwo

Autor
André Filipe de Domingues e Silva

Instituição
UP-FEUP

Factos & Números

0Outros Programas Financiamento

2016

27Artigos em revistas indexadas

2016

3Contratados de I&D

2016