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Sobre
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Sobre

Nascido na cidade do Porto a 7 de Novembro de 1962, licenciou-se em 1986 em Engenharia Electrotécnica na Faculdade de Engenharia da Universidade do Porto (FEUP). Completou o seu mestrado em Engenharia Electrotécnica na especialidade de Sistemas em 1991 e o seu doutoramento na mesma área em 1998. Entre 1986 e 1998 foi contratado como Assistente no Departamento de Engenharia Electrotécnica e de Computadores da FEUP. Atualmente é Professor Associado com Agregação do referido Departamento, desenvolvendo a sua atividade de investigação no INESC TEC onde é coordenador do Centro de Robótica Industrial e Sistemas Inteligentes. As sua principais áreas de investigação são a Robótica e o Controlo de Processos.

Tópicos
de interesse
Detalhes

Detalhes

048
Publicações

2022

A kinesthetic teaching approach for automating micropipetting repetitive tasks

Autores
Rocha, C; Dias, J; Moreira, AP; Veiga, G; Costa, P;

Publicação
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Abstract

2022

Active Perception Fruit Harvesting Robots — A Systematic Review

Autores
Magalhães, SA; Moreira, AP; Santos, FN; Dias, J;

Publicação
Journal of Intelligent and Robotic Systems: Theory and Applications

Abstract

2022

Augmented Reality for Human-Robot Collaboration and Cooperation in Industrial Applications: A Systematic Literature Review

Autores
Costa, GD; Petry, MR; Moreira, AP;

Publicação
SENSORS

Abstract
With the continuously growing usage of collaborative robots in industry, the need for achieving a seamless human-robot interaction has also increased, considering that it is a key factor towards reaching a more flexible, effective, and efficient production line. As a prominent and prospective tool to support the human operator to understand and interact with robots, Augmented Reality (AR) has been employed in numerous human-robot collaborative and cooperative industrial applications. Therefore, this systematic literature review critically appraises 32 papers' published between 2016 and 2021 to identify the main employed AR technologies, outline the current state of the art of augmented reality for human-robot collaboration and cooperation, and point out future developments for this research field. Results suggest that this is still an expanding research field, especially with the advent of recent advancements regarding head-mounted displays (HMDs). Moreover, projector-based and HMDs developed approaches are showing promising positive influences over operator-related aspects such as performance, task awareness, and safety feeling, even though HMDs need further maturation in ergonomic aspects. Further research should focus on large-scale assessment of the proposed solutions in industrial environments, involving the solution's target audience, and on establishing standards and guidelines for developing AR assistance systems.

2022

Active Perception Fruit Harvesting Robots - A Systematic Review

Autores
Magalhães, SA; Moreira, AP; dos Santos, FN; Dias, J;

Publicação
J. Intell. Robotic Syst.

Abstract

2022

Active Perception Fruit Harvesting Robots - A Systematic Review

Autores
Magalhaes, SA; Moreira, AP; dos Santos, FN; Dias, J;

Publicação
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS

Abstract
This paper studies the state-of-the-art of active perception solutions for manipulation in agriculture and suggests a possible architecture for an active perception system for harvesting in agriculture. Research and developing robots for agricultural context is a challenge, particularly for harvesting and pruning context applications. These applications normally consider mobile manipulators and their cognitive part has many challenges. Active perception systems look reasonable approach for fruit assessment robustly and economically. This systematic literature review focus in the topic of active perception for fruits harvesting robots. The search was performed in five different databases. The search resumed into 1034 publications from which only 195 publications where considered for inclusion in this review after analysis. We conclude that the most of researches are mainly about fruit detection and segmentation in two-dimensional space using evenly classic computer vision strategies and deep learning models. For harvesting, multiple viewpoint and visual servoing are the most commonly used strategies. The research of these last topics does not look robust yet, and require further analysis and improvements for better results on fruit harvesting.

Teses
supervisionadas

2021

Filling the maize yield gap based on precision agriculture – A Maxent approach

Autor
Marcos Alexandre Mota Norberto

Instituição
UP-FCUP

2021

Uma solução de Business Intelligence para a área académica da U. Porto

Autor
André lage Sobral

Instituição
UP-FCUP

2021

Presença espanhola em Portugal

Autor
Libânia Maria Pinto de Sousa

Instituição
UP-FEP

2021

Active Cooperative Perception for UAVs Teams

Autor
Guilherme Marques Amaral Silva

Instituição
UP-FEUP

2021

UVC Dose Mapping by Mobile Robots

Autor
Beatriz Inês Almeida Pinto

Instituição
UP-FEUP