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Sobre

Sobre

António Paulo Gomes Mendes Moreira é licenciado em Engenharia Eletrotécnica e de Computadores - FEUP (1986), opção Instrumentação Eletrónica, Mestre em Engenharia Eletrotécnica e de Computadores - Especialização em Sistemas pela FEUP (1991), Doutor em Engenharia Eletrotécnica e de Computadores (1998) e Agregado - FEUP (2017). Atualmente é Professor Catedrático no Departamento de Engenharia Eletrotécnica e de Computadores da Faculdade de Engenharia da Universidade do Porto. É também Investigador e Coordenador do CRIIS - Centro de Robótica Industrial e Sistemas Inteligentes e Diretor do iiLab - Laboratório de Indústria e Inovação do INESC TEC. Desenvolve investigação essencialmente em Robótica, Automação e Controlo, com ênfase na sua aplicação em projectos industriais e transferência de tecnologia. Participou ou participa ainda em 25 projetos científicos, sendo coordenador ou investigador responsável por 7 deles. O trabalho realizado nestes projectos gerou 40 projectos com empresas ou contratos de desenvolvimento e transferência de tecnologia, sendo o investigador principal em 18 destes projectos. Participou também no desenvolvimento de 18 protótipos e 2 patentes, das quais é coproprietário. Contribuiu para a criação de duas empresas spin-off. Mais pormenores em: https://www.cienciavitae.pt/portal/EB15-85A7-4A0D

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    António Paulo Moreira
  • Cargo

    Investigador Coordenador
  • Desde

    01 junho 2009
041
Publicações

2025

Integrating Multimodal Perception into Ground Mobile Robots

Autores
Sousa, RB; Sobreira, HM; Martins, JG; Costa, PG; Silva, MF; Moreira, AP;

Publicação
IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2025, Funchal, Portugal, April 2-3, 2025

Abstract
Multimodal perception systems enhance the robustness and adaptability of autonomous mobile robots by integrating heterogeneous sensor modalities, improving long-term localisation and mapping in dynamic environments and human-robot interaction. Current mobile platforms often focus on specific sensor configurations and prioritise cost-effectiveness, possibly limiting the flexibility of the user to extend the original robots further. This paper presents a methodology to integrate multimodal perception into a ground mobile platform, incorporating wheel odometry, 2D laser scanners, 3D Light Detection and Ranging (LiDAR), and RGBD cameras. The methodology describes the electronics design to power devices, firmware, computation and networking architecture aspects, and mechanical mounting for the sensory system based on 3D printing, laser cutting, and bending metal sheet processes. Experiments demonstrate the usage of the revised platform in 2D and 3D localisation and mapping and pallet pocket estimation applications. All the documentation and designs are accessible in a public repository. © 2025 IEEE.

2025

From Competition to Classroom: A Hands-on Approach to Robotics Learning

Autores
Lopes, MS; Ribeiro, JD; Moreira, AP; Rocha, CD; Martins, JG; Sarmento, JM; Carvalho, JP; Costa, PG; Sousa, RB;

Publicação
IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2025, Funchal, Portugal, April 2-3, 2025

Abstract
Robotics education plays a crucial role in developing STEM skills. However, university-level courses often emphasize theoretical learning, which can lead to decreased student engagement and motivation. In this paper, we tackle the challenge of providing hands-on robotics experience in higher education by adapting a mobile robot originally designed for competitions to be used in laboratory classes. Our approach integrates real-world robot operation into coursework, bridging the gap between simulation and physical implementation while maintaining accessibility. The robot's software is developed using ROS, and its effectiveness is assessed through student surveys. The results indicate that the platform increases student engagement and interest in robotics topics. Furthermore, feedback from teachers is also collected and confirmed that the platform boosts students' confidence and understanding of robotics. © 2025 IEEE.

2025

A Nonlinear Model Predictive Control Strategy for Trajectory Tracking of Omnidirectional Robots

Autores
Ribeiro, J; Sobreira, H; Moreira, A;

Publicação
Lecture Notes in Electrical Engineering

Abstract
This paper presents a novel Nonlinear Model Predictive Controller (NMPC) architecture for trajectory tracking of omnidirectional robots. The key innovation lies in the method of handling constraints on maximum velocity and acceleration outside of the optimization process, significantly reducing computation time. The controller uses a simplified process model to predict the robot’s state evolution, enabling real-time cost function minimization through gradient descent methods. The cost function penalizes position and orientation errors as well as control effort variation. Experimental results compare the performance of the proposed controller with a generic Proportional-Derivative (PD) controller and a NMPC with integrated optimization constraints. The findings reveal that the proposed controller achieves higher precision than the PD controller and similar precision to the NMPC with integrated constraints, but with substantially lower computational effort. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

2025

Designing and Developing a Fixed-Wing Tail-sitter Tethered VTOL UAV with Custom Autopilot: A MIMO $H_{\infty}$ Robust Control Approach

Autores
Safaee, A; Moreira, AP; Aguiar, AP;

Publicação
IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2025, Funchal, Portugal, April 2-3, 2025

Abstract
This article presents the development of a tethered fixed-wing tail-sitter VTOL (Vertical Take-Off and Landing) Unmanned Aerial Vehicle system. The design focuses on improving energy efficiency by utilizing the wings to harness wind power, similar to a kite, while maintaining VTOL functionality. A distinguishing feature is the purpose-built autopilot system, with custom hardware and software components specifically engineered for this application. The study presents the system identification process for obtaining five MIMO (Multiple-Input Multiple-Output) transfer functions that characterize the dynamics between roll-yaw commands and responses, including the tether angle feedback. To address the inherent coupling effects and uncertainties in the system, robust mixed sensitivity (H8) MIMO controllers are developed. The controllers were validated through both simulations and experimental flights, demonstrating effective performance in handling cross-coupling effects and maintaining stability under various operating conditions. According to flight test findings, the system can precisely manage the tether angle while adjusting for ground effect disturbances. This allows for accurate tethered navigation, a stable attitude, and the maintenance of an adequate yaw heading. © 2025 IEEE.

2024

Robotic Arm Development for a Quadruped Robot

Autores
Lopes, MS; Moreira, AP; Silva, MF; Santos, F;

Publicação
SYNERGETIC COOPERATION BETWEEN ROBOTS AND HUMANS, VOL 2, CLAWAR 2023

Abstract
Quadruped robots have gained significant attention in the robotics world due to their capability to traverse unstructured terrains, making them advantageous in search and rescue and surveillance operations. However, their utility is substantially restricted in situations where object manipulation is necessary. A potential solution is to integrate a robotic arm, although this can be challenging since the arm's addition may unbalance the whole system, affecting the quadruped locomotion. To address this issue, the robotic arm must be adapted to the quadruped robot, which is not viable with commercially available products. This paper details the design and development of a robotic arm that has been specifically built to integrate with a quadruped robot to use in a variety of agricultural and industrial applications. The design of the arm, including its physical model and kinematic configuration, is presented. To assess the effectiveness of the prototype, a simulation was conducted with a motion-planning algorithm based on the arm's inverse kinematics. The simulation results confirm the system's stability and the functionality of the robotic arm's movement.

Teses
supervisionadas

2023

Harvesting with active perception for open-field agricultural robotics

Autor
Sandro Augusto Costa Magalhães

Instituição
UP-FEUP

2023

Multi-Sensorial Simultaneous Localization and Mapping in Unmanned Aerial Vehicles

Autor
João Graça Martins

Instituição
UP-FEUP

2023

Multi-sensor approach for Power Lines Inspection with an Unmanned Aerial Vehicle

Autor
Tiago André Miranda dos Santos

Instituição
UP-FEUP

2023

Quadruped manipulator for potential agricultural applications

Autor
Maria Silva Lopes

Instituição
UP-FEUP

2023

Adaptive Grasping Planning: A Novel Unified and Modular Grasping Pipeline Architecture

Autor
João Pedro Carvalho de Souza

Instituição
UP-FEP