Detalhes
Nome
Eduardo SilvaCluster
Redes de Sistemas InteligentesCargo
Coordenador de TEC4Desde
01 dezembro 2010
Nacionalidade
PortugalCentro
Centro de Robótica e Sistemas AutónomosContactos
+351228340554
eduardo.silva@inesctec.pt
2021
Autores
Freitas, S; Silva, H; Silva, E;
Publicação
REMOTE SENSING
Abstract
2020
Autores
Fernandes, D; Pinheiro, F; Dias, A; Martins, A; Almeida, J; Silva, E;
Publicação
ROBOTICS IN EDUCATION: CURRENT RESEARCH AND INNOVATIONS
Abstract
Teaching robotics based on challenge of our daily lives is always more motivating for students and teachers. Several competitions of self-driving have emerged recently, challenging students and researchers to develop solutions addressing the autonomous driving systems. The Portuguese Festival Nacional de Robótica (FNR) Autonomous Driving Competition is one of those examples. Even though the competition is an exciting challenger, it requires the development of real robots, which implies several limitations that may discourage the students and compromise a fluid teaching process. The simulation can contribute to overcome this limitation and can assume an important role as a tool, providing an effortless and costless solution, allowing students and researchers to keep their focus on the main issues. This paper presents a simulation environment for FNR, providing an overall framework able to support the exploration of robotics topics like perception, navigation, data fusion and deep learning based on the autonomous driving competition. © Springer Nature Switzerland AG 2020.
2020
Autores
Teixeira, B; Silva, H; Matos, A; Silva, E;
Publicação
IEEE ACCESS
Abstract
2020
Autores
Barbosa, J; Dias, A; Almeida, J; Silva, E;
Publicação
FOURTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, ROBOT 2019, VOL 1
Abstract
The big growth of electrical demand by the countries required larger and more complex power systems, which have led to a greater need for monitoring and maintenance of these systems. To overcome this problem, UAVs equipped with appropriated sensors have emerged, allowing the reduction of the costs and risks when compared with traditional methods. The development of UAVs together with the great advance of the deep learning technologies, more precisely in the detection of objects, allowed to increase the level of automation in the process of inspection. This work presents an electrical assets monitoring system for detection of insulators and structures (poles and pylons) from images captured through a UAV. The proposed detection system is based on lightweight Convolutional Neural Networks and it is able to run on a portable device, aiming for a low cost, accurate and modular system, capable of running in real time. © 2020, Springer Nature Switzerland AG.
2020
Autores
Ferreira, A; Matias, B; Almeida, J; Silva, E;
Publicação
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
Abstract
Teses supervisionadas
2021
Autor
PAULO DUARTE VALENTE DE OLIVEIRA GOULÃO
Instituição
IPP-ISEP
2021
Autor
MURILLO PRESTES VILLA
Instituição
IPP-ISEP
2020
Autor
DIMPI RAJUBHAI PATEL
Instituição
IPP-ISEP
2019
Autor
JOÃO DAVID GUIMARÃES FIGUEIREDO DIAS
Instituição
IPP-ISEP
2018
Autor
LUÍS MIGUEL CUNHA CARDOSO
Instituição
IPP-ISEP
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.