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Robotics in Industry and Intelligent Systems

At CRIIS, we work closely with Companies, other Institutes and Universities, following the motto from Research and Development to Innovation, Design, Prototyping and Implementation.

At our Centre, we address the following main research areas: Navigation and Localisation of Mobile Robots, Intelligent Sensors and Control of Dynamical Systems, 2D/3D Industrial Vision and Advanced Sensing, Mobile Manipulators, Special Structures and Architectures for Robots, Human Robot Interfacing and Augmented Reality, Future Industrial Robotics and Collaborative Robots, Vertical Integration, IoT, and Industry 4.0.

Latest News
Industry and Innovation

International conference on innovation promoted by COTEC with the collaboration of INESC TEC

On 8 July, INESC TEC participated in the 16th COTEC Innovation Summit, with the theme "Leading 4.0 – Highway to manufacture value with people and intelligent machines”. 

19th July 2019

Industry and Innovation

Industrial Robotics presented to students in Vila Real

On May 10, Luís Santos, Pranjali Shinde and Jorge Mendes, collaborators of INESC TEC’s Centre for Robotics and Intelligent Systems (CRIIS), participated in an event designed to high school students, in order to present the work of the University, namely in the application of technology in real contexts.

18th June 2019

INESC TEC debuts on the 360 TECH INDUSTRY

Under the approach to the Industry sector, INESC TEC was present on the first edition of 360 TECH INDUSTRY – International Trade Fair of Industry 4.0, Robotics, Automation and Composites, which took place between 16 and 18 May at Exponor, in Porto.

18th June 2019

Industry and Innovation

INESC TEC inaugurates laboratory for industry and innovation

iiLab’s mission is to demonstrate and to disclose concepts and advanced technologies for the digitalisation of production including robotics, automation, simulation, virtual and augmented reality, and decision support and cyber-physical systems.

13th June 2019

Industry and Innovation

INESC TEC’s researchers receive Best Paper Award at the ICARSC’2019 Conference

Articles of researchers of INESC TEC’s Centre for Robotics and Intelligent Systems won the Industrial Robot Best Paper Award, which was promoted at the ICARSC’2019 conference.

05th June 2019

Interest Topics
047

Featured Projects

DEMETER

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

2019-2023

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

Refinação4.0

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

2018-2019

MetBots

Metabolomic robots with self-learning artificial intelligence for precision agriculture

2018-2020

SAFER

Safery verification for robotic software

2018-2021

COBOTIS

Human-robot interaction for collaborative robotics

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

Footwear, Advanced Materials, Equipment's and Software Technologies

2017-2020

PRODUTECH_SIF

Soluções para a Indústria de Futuro

2017-2020

Water4Ever

Optimizing water use in agriculture to preserve soil and water resources

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

2017-2019

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

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

Advances in FOrestry Control and aUtomation Systems in Europe

2014-2016

CLARISSA

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

2014-2016

STAMINA

Sustainable and reliable robotics for part handling in manufacturing automation

2013-2017

Team
003

Laboratories

Laboratory of Industrial Robotics and Automation

Laboratory of Mobile Robotics and Internal Logistics

Laboratory of Robotics for Agriculture and Forestry

Publications

CRIIS Publications

View all Publications

2019

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

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

Publication
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

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

Publication
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

Prototyping and Programming a Multipurpose Educational Mobile Robot - NaSSIE

Authors
Pinto, VH; Monteiro, JM; Gonçalves, J; Costa, P;

Publication
Robotics in Education - Advances in Intelligent Systems and Computing

Abstract

2019

Introduction to the Special Issue “Robotica 2016”

Authors
Cunha, B; Lima, J; Silva, M; Leitao, P;

Publication
Journal of Intelligent and Robotic Systems: Theory and Applications

Abstract

2019

Map-Matching Algorithms for Robot Self-Localization: A Comparison Between Perfect Match, Iterative Closest Point and Normal Distributions Transform

Authors
Sobreira, H; Costa, CM; Sousa, I; Rocha, L; Lima, J; Farias, PCMA; Costa, P; Paulo Moreira, AP;

Publication
Journal of Intelligent and Robotic Systems: Theory and Applications

Abstract
The self-localization of mobile robots in the environment is one of the most fundamental problems in the robotics navigation field. It is a complex and challenging problem due to the high requirements of autonomous mobile vehicles, particularly with regard to the algorithms accuracy, robustness and computational efficiency. In this paper, we present a comparison of three of the most used map-matching algorithms applied in localization based on natural landmarks: our implementation of the Perfect Match (PM) and the Point Cloud Library (PCL) implementation of the Iterative Closest Point (ICP) and the Normal Distribution Transform (NDT). For the purpose of this comparison we have considered a set of representative metrics, such as pose estimation accuracy, computational efficiency, convergence speed, maximum admissible initialization error and robustness to the presence of outliers in the robots sensors data. The test results were retrieved using our ROS natural landmark public dataset, containing several tests with simulated and real sensor data. The performance and robustness of the Perfect Match is highlighted throughout this article and is of paramount importance for real-time embedded systems with limited computing power that require accurate pose estimation and fast reaction times for high speed navigation. Moreover, we added to PCL a new algorithm for performing correspondence estimation using lookup tables that was inspired by the PM approach to solve this problem. This new method for computing the closest map point to a given sensor reading proved to be 40 to 60 times faster than the existing k-d tree approach in PCL and allowed the Iterative Closest Point algorithm to perform point cloud registration 5 to 9 times faster. © 2018 Springer Science+Business Media B.V., part of Springer Nature

Supervised Theses

2018

Produção de lúpulo nacional: uma estratégia para a sustentabilidade

Author
Sandra Cristina Pereira Afonso

Institution
UP-FCUP

2018

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

Author
Sosdito Estevao Mananze

Institution
UP-FCUP

2018

Design of a low power transmitter for UWB applications

Author
Iman Kianpour

Institution
UP-FEUP

2018

Development of robotic manipulators for scalable production lines

Author
Paulo Diogo Carvalho Ribeiro

Institution
UP-FEUP

2018

Ferramenta para Desenvolvimento de Inteligência em Jogos Simulados em ambiente Simtwo

Author
André Filipe de Domingues e Silva

Institution
UP-FEUP

Facts & Figures

169R&D Services and Consulting (k€)

2016

657Turnover (k€)

2016

0Concluded PhD theses

2016