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Tópicos
de interesse
Detalhes

Detalhes

025
Publicações

2022

A kinesthetic teaching approach for automating micropipetting repetitive tasks

Autores
Rocha, C; Dias, J; Moreira, AP; Veiga, G; Costa, P;

Publicação
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Abstract

2022

Using Simulation to Evaluate a Tube Perception Algorithm for Bin Picking

Autores
Leao, G; Costa, CM; Sousa, A; Reis, LP; Veiga, G;

Publicação
ROBOTICS

Abstract
Bin picking is a challenging problem that involves using a robotic manipulator to remove, one-by-one, a set of objects randomly stacked in a container. In order to provide ground truth data for evaluating heuristic or machine learning perception systems, this paper proposes using simulation to create bin picking environments in which a procedural generation method builds entangled tubes that can have curvatures throughout their length. The output of the simulation is an annotated point cloud, generated by a virtual 3D depth camera, in which the tubes are assigned with unique colors. A general metric based on micro-recall is proposed to compare the accuracy of point cloud annotations with the ground truth. The synthetic data is representative of a high quality 3D scanner, given that the performance of a tube modeling system when given 640 simulated point clouds was similar to the results achieved with real sensor data. Therefore, simulation is a promising technique for the automated evaluation of solutions for bin picking tasks.

2021

Force control heuristics for surpassing pose uncertainty in mobile robotic assembly platforms

Autores
Moutinho, D; Rebelo, P; Costa, C; Rocha, L; Veiga, G;

Publicação
2021 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC)

Abstract

2021

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

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

Publicação
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.

2021

On the development of a collaborative robotic system for industrial coating cells

Autores
Arrais, R; Costa, CM; Ribeiro, P; Rocha, LF; Silva, M; Veiga, G;

Publicação
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Abstract

Teses
supervisionadas

2021

NRfinder: A pipeline for the characterization of the number and type of nuclear receptors in a genomic sequence

Autor
Marcos António Pereira Domingues

Instituição
UP-FCUP

2020

Desenvolvimento de uma solução de bin-picking robotizada

Autor
Nuno Alexandre Moreira do Rosário

Instituição
UP-FEUP

2020

Force based robotized assembly – mobile manipulator use case

Autor
Duarte Alão Magalhães Silva Moutinho

Instituição
UP-FEUP

2020

Open Scalable Production System: An Industry 4.0 Framework for Cyber-Physical Systems

Autor
Rafael Lirio Arrais

Instituição
UP-FEUP

2020

Desenvolvimento de uma aplicação para geração automática de código para o PLC de controlo de elevadores

Autor
Cristina Lírio Ferreira

Instituição
UP-FEUP