INESC TEC
INESC TEC
INESC TEC
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Filipe Neves Santos

Filipe Neves Santos

TEC4 Coordinator

Filipe Neves dos Santos was born in São Paio de Oleiros, Portugal, in 1979. He olds a Licenciatura (5-year degree) in Electrical and Computer Engineering in 2003 from Instituto Superior de Engenharia do Porto (ISEP), a M.Sc. in Electrical and Computer Engineering from the Instituto Superior Técnico (IST) da Universidade Técnica de Lisboa, in 2007, and received the PhD degree in Electrical and Computer Engineering at the Faculdade de Engenharia (FEUP), Universidade do Porto, Portugal, in 2014. His professional passion is to develop autonomous robots and machinery to solve real problems, desires and needs of our society and to contribute for self-sustainability and fairness of the global economy. Actually, He is focused in developing and researching robotic solutions for agriculture and forestry sector, where is required a higher efficiency for our world self-sustainability. Considering his closer regional reality, he have setup the goal to promote agricultural robotic based projects and develop robots that can operate fully autonomously and safely in steep-slope scenarios, which is a common reality of North of Portugal and in other large number of world regions. As so, he is interested in explore and develop robots for specific agricultural and forestall tasks such as: monitoring (by ground), spraying, logistics, pruning, and selective harvesting. The successfully execution of these task is largely dependent on the robustness of specific robotic systems, such as: - Visual Perception; - Navigation (localization, mapping and path planning); and - Manipulation and end tools. For that reason Visual Perception and Navigation are his main research fields inside of robotics research. His formation in Electronics and Computer Engineer (Bachelor (old-one of 5 years) MSc (sensor fusion), PhD (semantic mapping) ), experience of 4 years as entrepreneur (technological startup), 8 year as robotics researcher, 5 years as manager (in supporting tasks in a family enterprise), and 6 year as electronics technician will help him to successfully contribute for the agricultural and forestall robotics future.

Publications

Plant Leaf Disease Detection Using Deep Learning: A Multi-Dataset Approach

Krishna, MS;Machado, P;Otuka, RI;Yahaya, SW;Neves dos Santos, F;Ihianle, IK;

2024

Early plant disease diagnosis through handheld UV-Vis transmittance spectrometer with DD-SIMCA one-class classification and MCR-ALS bilinear decomposition

Reis-Pereira, M;Mazivila, SJ;Tavares, F;dos Santos, FN;Cunha, M;

2024

SMART AGRICULTURAL TECHNOLOGY

Pruning End-Effectors State of the Art Review

Oliveira, F;Tinoco, V;Valente, A;Pinho, TM;Cunha, JB;Santos, F;

2024

Progress in Artificial Intelligence - 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3-6, 2024, Proceedings, Part I

Deep learning based approach for actinidia flower detection and gender assessment

Pinheiro, I;Moreira, G;Magalhaes, S;Valente, A;Cunha, M;dos Santos, FN;

2024

SCIENTIFIC REPORTS

View all publications

Supervised Theses

Grasping and manipulation with active perception for open-field agricultural robotics

Sandro Augusto Costa Magalhães

D - 2020

UP-FEUP

Advanced 2.5D Path Planning for agricultural robots

Luís Carlos Feliz Santos

D - 2020

UTAD-ECT

Localization and Mapping based on Semantic and Multi-Layer Maps Concepts

André Silva Pinto de Aguiar

D - 2020

UTAD-ECT

ForestMP: Multimodal perception system for robotics in forestry applications

Daniel Queirós da Silva

D - 2022

UTAD-ECT

See more supervised theses

Centres

Robotics in Industry and Intelligent Systems

At the Centre for Robotics and Intelligent Systems, we develop innovative solutions to leverage robotics in the industrial, agricultural, and forestry contexts, driving the digital transformation of the industry. We take a practical approach - from design to deployment - to test the navigation and localisation of mobile robots, explore advances in 2D/3D industrial vision and advanced detection, while also focusing on industrial and collaborative robotics, as well as human-robot interfaces. Our TRIBE LAB is fertile ground for innovative ideas about the agriculture of the future; we develop prototypes and promote excellence in agricultural robotics and IoT technology: with prototypes, advanced sensors (LiDAR, AI cameras), and rapid prototyping tools, we accelerate the development of solutions for the agroforestry sector. We are also present at the iiLab, where we combine applied research, technological demonstration, and controlled environment testing, promoting the integration of emerging technologies into industry. From intelligent robotic cells and cyber-physical systems to data analysis and AI, it is an innovation space where companies can experiment with and validate solutions for the factory of the future. With a multidisciplinary team, and following European agendas, our research work combines fundamental science and application, impacting the design of solutions for Industry 4.0, fostering competitiveness and the digital transformation of the sector.

Robotics in Industry and Intelligent Systems

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+351220413317
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