Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
About
Download Photo HD

About

Born at Porto, Portugal, April  6, 1973, received the M.Sc.in Electrical and Computer Engineering on Faculty of Engineering of University of Porto, Portugal in 1999. He obtained a Ph.D. in Electrical and Computer Engineering on Faculty of Engineering of University of Porto in the area of Control and Robotics, with the thesis “Planning Cooperative tasks and trajectories in Multiple Robots” in 2011. Presently he is a Professor at Computers and Electrical Engineering Department of the Oporto University. He is also a researcher in Robotic and Intelligent Systems of the INESC-TEC (Institute for Systems and Computer Engineering of Porto, Portugal). His research interests are in the ï¬�eld of robotics and automation: path planning, obstacle avoidance, simulation, navigation, manipulator, mobile manipulators. 

Interest
Topics
Details

Details

006
Publications

2021

Micromouse 3D simulator with dynamics capability: a Unity environment approach

Authors
Zawadniak, PVF; Piardi, L; Brito, T; Lima, J; Costa, P; Monteiro, ALR; Costa, P; Pereira, AI;

Publication
SN APPLIED SCIENCES

Abstract
The micromouse competition has been gaining prominence in the robotic atmosphere, due to the challenging and multidisciplinary characteristics provided by the teams' duels, being a gateway for those who intend to deepen their studies in autonomous robotics. In this context, this paper presents a realistic micromouse simulator developed with Unity software, a widely game engine with dynamics and 3D development platform used. The developed simulator has hardware-in-the-loop capabilities, aims to be simple to use, it can be customizable, and designed to be as similar as possible to the real robot configurations. In this way, the proposed simulator requires few modifications to port the microcontroller code to a real robot. Therefore, the framework presented in this work allows the user to simulate the development of new algorithm strategies dedicated to competition and also hardware updates. The simulation supports several mazes, from previous competitions and has the possibility to add different mazes elaborated by the user. Thus, the features and functionality of the simulator can serve to accelerate the project's development of the beginning and advanced competitors, using real models to reduce the gap between the mouse robot behavior in the simulation and the reality. The developed simulation environment is available to the community.

2021

Multi AGV Coordination Tolerant to Communication Failures

Authors
Matos, D; Costa, P; Lima, J; Costa, P;

Publication
Robotics

Abstract
Most path planning algorithms used presently in multi-robot systems are based on offline planning. The Timed Enhanced A* (TEA*) algorithm gives the possibility of planning in real time, rather than planning in advance, by using a temporal estimation of the robot’s positions at any given time. In this article, the implementation of a control system for multi-robot applications that operate in environments where communication faults can occur and where entire sections of the environment may not have any connection to the communication network will be presented. This system uses the TEA* to plan multiple robot paths and a supervision system to control communications. The supervision system supervises the communication with the robots and checks whether the robot’s movements are synchronized. The implemented system allowed the creation and execution of paths for the robots that were both safe and kept the temporal efficiency of the TEA* algorithm. Using the Simtwo2020 simulation software, capable of simulating movement dynamics and the Lazarus development environment, it was possible to simulate the execution of several different missions by the implemented system and analyze their results.

2021

A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario

Authors
Santos, J; Rebelo, PM; Rocha, LF; Costa, P; Veiga, G;

Publication
Robotics

Abstract
A multi-AGV based logistic system is typically associated with two fundamental problems, critical for its overall performance: the AGV’s route planning for collision and deadlock avoidance; and the task scheduling to determine which vehicle should transport which load. Several heuristic functions can be used according to the application. This paper proposes a time-based algorithm to dynamically control a fleet of Autonomous Guided Vehicles (AGVs) in an automatic warehouse scenario. Our approach includes a routing algorithm based on the A* heuristic search (TEA*—Time Enhanced A*) to generate free-collisions paths and a scheduling module to improve the results of the routing algorithm. These modules work cooperatively to provide an efficient task execution time considering as basis the routing algorithm information. Simulation experiments are presented using a typical industrial layout for 10 and 20 AGVs. Moreover, a comparison with an alternative approach from the state-of-the-art is also presented.

2020

Optimal automatic path planner and design for high redundancy robotic systems

Authors
Tavares, P; Marques, D; Malaca, P; Veiga, G; Costa, P; Moreira, AP;

Publication
INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION

Abstract
Purpose In the vast majority of the individual robot installations, the robot arm is just one piece of a complex puzzle of components, such as grippers, jigs or external axis, that together compose an industrial robotic cell. The success of such installations is very dependent not only on the selection of such components but also on the layout and design of the final robotic cell, which are the main tasks of the system integrators. Consequently, successful robot installations are often empirical tasks owing to the high number of experimental combinations that could lead to exhaustive and time-consuming testing approaches. Design/methodology/approach A newly developed optimized technique to deal with automatic planning and design of robotic systems is proposed and tested in this paper. Findings The application of a genetic-based algorithm achieved optimal results in short time frames and improved the design of robotic work cells. Here, the authors show that a multi-layer optimization approach, which can be validated using a robotic tool, is able to help with the design of robotic systems. Originality/value To date, robotic solutions lack flexibility to cope with the demanding industrial environments. The results presented here formalize a new flexible and modular approach, which can provide optimal solutions throughout the different stages of design and execution control of any work cell.

2020

Path Planning Aware of Robot’s Center of Mass for Steep Slope Vineyards

Authors
Santos, L; Santos, F; Mendes, J; Costa, P; Lima, J; Reis, R; Shinde, P;

Publication
Robotica

Abstract
SummarySteep slope vineyards are a complex scenario for the development of ground robots. Planning a safe robot trajectory is one of the biggest challenges in this scenario, characterized by irregular surfaces and strong slopes (more than 35°). Moving the robot through a pile of stones, spots with high slope or/and with wrong robot yaw may result in an abrupt fall of the robot, damaging the equipment and centenary vines, and sometimes imposing injuries to humans. This paper presents a novel approach for path planning aware of center of mass of the robot for application in sloppy terrains. Agricultural robotic path planning (AgRobPP) is a framework that considers the A* algorithm by expanding inner functions to deal with three main inputs: multi-layer occupation grid map, altitude map and robot’s center of mass. This multi-layer grid map is updated by obstacles taking into account the terrain slope and maximum robot posture. AgRobPP is also extended with algorithms for local trajectory replanning during the execution of a trajectory that is blocked by the presence of an obstacle, always assuring the safety of the re-planned path. AgRobPP has a novel PointCloud translator algorithm called PointCloud to grid map and digital elevation model (PC2GD), which extracts the occupation grid map and digital elevation model from a PointCloud. This can be used in AgRobPP core algorithms and farm management intelligent systems as well. AgRobPP algorithms demonstrate a great performance with the real data acquired from AgRob V16, a robotic platform developed for autonomous navigation in steep slope vineyards.

Supervised
thesis

2020

Robô de baixo custo para monitorização de colheitas em contexto de montanha

Author
André Miguel Mota Costa Oliveira

Institution
UP-FEUP

2020

Multi AGV coordination tolerant to communication failures

Author
Diogo Miguel Rodrigues Matos

Institution
UP-FEUP

2019

Controlo de Manipulador Paralelo para Montagem de Rolhas Capsuladas

Author
Pedro Manuel Morais Martins Santos

Institution
UP-FEUP

2019

Projection Mapping aplicada à industrial de Fabricação de estruturas para armazenamento alimentar

Author
Carlos Manuel Borges Silva

Institution
UP-FEUP

2019

Sistema automatizado de produção de rolhas capsuladas

Author
Francisco Manuel Silva Matos

Institution
UP-FEUP