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Sobre

Sobre

Filipe Neves dos Santos nasceu em São Paio de Oleiros, em Portugal, em 1979. Doutorado em engenharia eletrotécnica e computadores (2014) pela Faculdade de Engenharia da Universidade do Porto (FEUP), Mestrado em engenharia eletrotécnica e computadores – automação e robótica (2007) pelo Instituto Superior Técnico (IST) da Universidade Técnica de Lisboa, licenciado em engenharia eletrotécnica e computadores (2003) pelo Instituto Superior de Engenharia do Porto (ISEP). Profissionalmente é apaixonado pela investigação e desenvolvimento de soluções robóticas e automatização que permitam resolver problemas reais, desejos e necessidades da nossa sociedade e contribuir para a autossustentabilidade e justiça da economia global. Neste momento a sua principal linha de investigação centra-se no desenvolvimento de soluções robotizadas para o setor agrícola e florestal, onde é necessária uma maior eficiência para a nossa autossustentabilidade mundial. Em 2013, considerando a realidade de Portugal e os principais roteiros de inovação, estruturou um roteiro de investigação centrado no desenvolvimento de robótica e sistemas inteligentes para o contexto agrícola e florestal. Nomeadamente, em contextos de declive acentuado e sem acesso a GPS/GNSS, onde são requeridas a execução de tarefas tais como: monitorização (por terra), pulverização de precisão, logística, poda e colheita seletiva. A execução eficiente destas tarefas depende em grande parte da robustez dos sistemas robóticos específicos, tais como:  Perceção visual;- Navegação (localização, mapeamento e planeamento de caminhos seguros); e  Manipulação e ferramentas especificas. A sua formação em engenharia MSc (fusão sensorial e GPS/GNSS), PhD (mapeamento e localização semântica), experiência de 4 anos como empreendedor (startup tecnológica), participação e coordenação de projetos de investigação na área da robótica durante mais de 12 anos, 5 anos de experiência em tarefas de contabilidade e gestão (empresa familiar), e 6 anos como técnico de eletrónica fornecerão o saber saber e saber fazer para que possa contribuir para o sucesso do futuro da robótica agrícola.

Tópicos
de interesse
Detalhes

Detalhes

017
Publicações

2016

Towards a Reliable Robot for Steep Slope Vineyards Monitoring

Autores
dos Santos, FN; Sobreira, H; Campos, D; Morais, R; Moreira, AP; Contente, O;

Publicação
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS

Abstract
Develop ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge. Because of two main reasons: harsh condition of the terrain and unstable localization accuracy got from Global Positioning Systems (GPS). This paper presents a hybrid SLAM (VineSLAM) considering low cost landmarks to increase the robot localization accuracy, robustness and redundancy on these steep slope vineyards. Also, we present a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environment. Test results got in a simulated and in a real test case supports the proposed approach and robot.

2016

Vine trunk detector for a reliable robot localization system

Autores
Mendes, J; dos Santos, FN; Ferraz, N; Couto, P; Morais, R;

Publicação
2016 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2016)

Abstract
Develop 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 got from Global Positioning Systems (GPS). For this context, a reliable localization system requires a high density of natural/artificial features and an accurate detector. This paper presents a novel visual detector for Vineyards Trunks and Masts (ViTruDe). The ViTruDe detector was developed considering the constrains of a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environment. The obtained results with real data shows an accuracy higher than 95% for all tested configurations. The training and test data are made public for future research work. This approach is a contribution for an accurate and reliable localization system that is GPS-free.

2015

Towards a Reliable Monitoring Robot for Mountain Vineyards

Autores
dos Santos, FN; Sobreira, H; Campos, D; Morais, R; Moreira, AP; Contente, O;

Publicação
2015 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)

Abstract
Crop monitoring and harvesting by ground robots on mountain vineyards is an intrinsically complex challenge, due to two main reasons: harsh conditions of the terrain and reduced time availability and unstable localization accuracy of the GPS system. In this paper is presented a cost effective robot that can be used on these mountain vineyards for crop monitoring tasks. Also it is explored a natural vineyard feature as the input of a standard 2D simultaneous localization and mapping approach (SLAM) for feature-based map extraction. In order to be possible to evaluate these natural features for mapping and localization purposes, a virtual scenario under ROS/Gazebo has been built and described. A low cost artificial landmark and an hybrid SLAM is proposed to increase the localization accuracy, robustness and redundancy on these mountain vineyards. The obtained results, on the simulation framework, validates the use of a localization system based on natural mountain vineyard features.

2015

Visual Signature for Place Recognition in Indoor Scenarios

Autores
dos Santos, FN; Costa, PC; Moreira, AP;

Publicação
CONTROLO'2014 - PROCEEDINGS OF THE 11TH PORTUGUESE CONFERENCE ON AUTOMATIC CONTROL

Abstract
Recognizing a place with a visual glance is the first capacity used by humans to understand where they are. Making this capacity available to robots will make it possible to increase the redundancy of the localization systems available in the robots, and improve semantic localization systems. However, to achieve this capacity it is necessary to build a robust visual signature that could be used by a classifier. This paper presents a new approach to extract a global descriptor from an image that can be used as the visual signature for indoor scenarios. This global descriptor was tested using videos acquired from three robots in three different indoor scenarios. This descriptor has shown good accuracy and computational performance when compared to other local and global descriptors.

2014

A visual place recognition procedure with a Markov chain based filter

Autores
dos Santos, FN; Costa, P; Moreira, AP;

Publicação
2014 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)

Abstract
Recognizing a place with a visual glance is the first capacity used by humans to understand where they are. Making this capacity available to robots will make it possible to increase the redundancy of the localization systems available in the robots, and improve semantic localization systems. However, to achieve this capacity it is necessary to build a robust visual place recognition procedure that could be used by an indoor robot. This paper presents an approach that from a single image estimates the robot location in the semantic space. This approach extracts from each camera image a global descriptor, which is the input of a Support Vector Machine classifier. In order to improve the classifier accuracy a Markov chain formalism was considered to constraint the probability flow according the place connections. This approach was tested using videos acquired from three robots in three different indoor scenarios - with and without the Markov chain filter. The use of Markov chain filter has shown a significantly improvement of the approach accuracy.

2013

Fast 3D Map Matching Localisation Algorithm

Autores
Pinto, M; Moreira, AP; Matos, A; Sobreira, H; Santos, F;

Publicação
Journal of Automation and Control Engineering - JOACE

Abstract

Teses
supervisionadas

2016

Sistema integrado, adaptativo e inteligente para a gestão energética de robôs

Autor
Nuno André Ferreira Ferraz

Instituição
UTAD