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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

004
Publications

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.

2019

Collaborative Welding System using BIM for Robotic Reprogramming and Spatial Augmented Reality

Authors
Tavares, P; Costa, CM; Rocha, L; Malaca, P; Costa, P; Moreira, AP; Sousa, A; Veiga, G;

Publication
Automation in Construction

Abstract
The optimization of the information flow from the initial design and through the several production stages plays a critical role in ensuring product quality while also reducing the manufacturing costs. As such, in this article we present a cooperative welding cell for structural steel fabrication that is capable of leveraging the Building Information Modeling (BIM) standards to automatically orchestrate the necessary tasks to be allocated to a human operator and a welding robot moving on a linear track. We propose a spatial augmented reality system that projects alignment information into the environment for helping the operator tack weld the beam attachments that will be later on seam welded by the industrial robot. This way we ensure maximum flexibility during the beam assembly stage while also improving the overall productivity and product quality since the operator no longer needs to rely on error prone measurement procedures and he receives his tasks through an immersive interface, relieving him from the burden of analyzing complex manufacturing design specifications. Moreover, no expert robotics knowledge is required to operate our welding cell because all the necessary information is extracted from the Industry Foundation Classes (IFC), namely the CAD models and welding sections, allowing our 3D beam perception systems to correct placement errors or beam bending, which coupled with our motion planning and welding pose optimization system ensures that the robot performs its tasks without collisions and as efficiently as possible while maximizing the welding quality. © 2019 Elsevier B.V.

2019

Path Planning approach with the extraction of Topological Maps from Occupancy Grid Maps in steep slope vineyards

Authors
Santos, L; Santos, FN; Magalhaes, S; Costa, P; Reis, R;

Publication
19th IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2019

Abstract
Robotic platforms are being developed for precision agriculture, to execute repetitive and long term tasks. Autonomous monitoring, pruning, spraying and harvesting are some of these agricultural tasks, which requires an advanced path planning system aware of maximum robot capabilities (mobile platform and arms), terrain slopes and plant/fruits position. The state of the art path planning systems have two limitations: are not optimized for large regions and the path planning is not aware of agricultural tasks requirements. This work presents two solutions to overcome these limitations. It considers the VGR2TO (Vineyard Grid Map to Topological) approach to extract from a 2D grid map a topological map, to reduce the total amount of memory needed by the path planning algorithm and to reduce path search space. Besides, introduces an extension to the chosen algorithm, the Astar algorithm, to ensure a safe path and a maximum distance from the vine trees to enable robotic operations on the tree and its fruits. © 2019 IEEE.

2019

Path planning optimization for a mobile manipulator

Authors
Silva, G; Costa, P; Rocha, L; Lima, J;

Publication
AIP Conference Proceedings

Abstract
Nowadays, mobile manipulators are increasing its popularity on modern industries due to their ability to enhance process flexibility and performance. Mobile manipulators are a wide field of research and one of the main directions is trying to control the whole system as a single device. In this context, this paper addresses the problem of path planning of the end-effector of a mobile manipulator. The proposed approach is based on the integration of the kinematic chain of both the manipulator and the omni-directional base. At the end, a collision-free path planner for the mobile manipulator in complex and known environments with obstacles using A* is derived. © 2019 Author(s).

Supervised
thesis

2019

Robotic Manipulation of Deformable Objects

Author
Mauricio García Hernández

Institution
UP-FEUP

2019

Sistema automatizado de produção de rolhas capsuladas

Author
Francisco Manuel Silva Matos

Institution
UP-FEUP

2019

Controlo de Manipulador Paralelo para Montagem de Rolhas Capsuladas

Author
Pedro Manuel Morais Martins Santos

Institution
UP-FEUP

2019

Cost-effective robot for steep slope crops monitoring

Author
Filipe Peixoto Mendes

Institution
UP-FEUP

2019

Optimal Automatic Path Planning and Design for High Redundancy Robotic Systems

Author
Pedro Miguel Santos Tavares

Institution
UP-FEUP