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Sobre

Sobre

Marcelo R. Petry é investigador e educador no Centro de Robótica Industrial e Sistemas Inteligentes do INESC TEC (Portugal). A sua área investigação situa-se na intersecção da robótica, visão computacional e realidade extendida, visando a aplicação de robôs na produção, logística, inspeção e assistência humana. Marcelo licenciou-se em Engenharia de Controle e Automação pela Pontifícia Universidade Católica do Rio Grande do Sul em 2008 (Brasil) e obteve seu doutoramento em Engenharia Informática pela Universidade do Porto em 2013 (Portugal). Anteriormente, foi Professor Auxiliar da Universidade Federal de Santa Catarina e pesquisador do INESC P&D Brasil (2014 a 2019).

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Marcelo Petry
  • Cargo

    Investigador Sénior
  • Desde

    04 janeiro 2010
024
Publicações

2024

Assessment of Multiple Fiducial Marker Trackers on Hololens 2

Autores
Costa, GM; Petry, MR; Martins, JG; Moreira, APGM;

Publicação
IEEE ACCESS

Abstract
Fiducial markers play a fundamental role in various fields in which precise localization and tracking are paramount. In Augmented Reality, they provide a known reference point in the physical world so that AR systems can accurately identify, track, and overlay virtual objects. This accuracy is essential for creating a seamless and immersive AR experience, particularly when prompted to cope with the sub-millimeter requirements of medical and industrial applications. This research article presents a comparative analysis of four fiducial marker tracking algorithms, aiming to assess and benchmark their accuracy and precision. The proposed methodology compares the pose estimated by four algorithms running on Hololens 2 with those provided by a highly accurate ground truth system. Each fiducial marker was positioned in 25 sampling points with different distances and orientations. The proposed evaluation method is not influenced by human error, relying only on a high-frequency and accurate motion tracking system as ground truth. This research shows that it is possible to track the fiducial markers with translation and rotation errors as low as 1.36 mm and 0.015 degrees using ArUco and Vuforia, respectively.

2024

A Study of Virtual Reality Applied to Welder Training

Autores
Couto, M; Petry, MR; Silva, MF;

Publicação
TOWARDS A HYBRID, FLEXIBLE AND SOCIALLY ENGAGED HIGHER EDUCATION, VOL 2, ICL2023

Abstract
Welding is a challenging, risky, and time-consuming profession. Recently, there has been a documented shortage of trained welders, and as a result, the market is pushing for an increase in the rate at which new professionals are trained. To address this growing demand, training institutions are exploring alternative methods to train future professionals. The emergence of virtual reality technologies has led to initiatives to explore their potential for welding training. Multiple studies have suggested that virtual reality training delivers comparable, or even superior, results when compared to more conventional approaches, with shorter training times and reduced costs in consumables. This paper conducts a comprehensive review of the current state of the field of welding simulators. This involves exploring the different types of welding simulators available and evaluating their effectiveness and efficiency in meeting the learning objectives of welding training. The aim is to identify gaps in the literature, suggest future research directions, and promote the development of more effective and efficient welding simulators in the future. The research also seeks to develop a categorical system for evaluating and comparing welding simulators. This system will enable a more systematic and objective analysis of the features and characteristics of each simulator, identifying the essential characteristics that should be included in each level of classification.

2024

Automating Lateral Shoe Roughing through a Robotic Manipulator Programmed by Demonstration

Autores
Ventuzelos, V; Petry, MR; Rocha, LF;

Publicação
2024 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
The footwear industry is known for its longstanding traditional production methods that require intense manual labor. Roughing, for example, is regarded as one of the significant and critical operations in shoe manufacturing and consists of using abrasive tools to remove a thin layer of the shoe's surface, creating a slightly roughened texture that provides a better surface area for adhesion. As such, workers are typically subjected to hazardous substances (i.e., dust, chromium), repetitive strain injuries, and ergonomic challenges. Although robots can automate repetitive tasks and perform with high precision and consistency, the footwear industry is usually reluctant to employ industrial robots due to the need for restructuring. This paper addresses the challenge of re-designing the lateral roughing of uppers to allow robot-assisted manufacturing with minimal modifications in the manufacturing process. The proposed innovative system employs a robotic manipulator to perform roughing based on data collected from preceding manufacturing steps. Workers marking the mesh line of each sole-upper pair can simultaneously teach the manipulator path for that same pair, using a programming-by-demonstration approach. Multiple paths were collected by outlining a piece of footwear, converted into robot instructions, and deployed on a simulated and real industrial manipulator. The key findings of this research showcase the capability of the proposed solution to replicate collected paths accurately, indicating potential applications not only in roughing processes but also in similar tasks like primer and adhesive application.

2024

A Multi-User Multi-Robot Collaboration through Augmented Reality

Autores
Martins, JG; Costa, GM; Petry, MR; Costa, P; Moreira, AP;

Publicação
2024 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
Current industrial environments have multiple robots working alongside humans, thus providing an operator the ability to perceive the robot's workspace correctly and to anticipate its intentions and movements through the visualization of the robot's digital twin is of utmost importance for safe and productive human-robot collaboration scenarios. Much has been studied regarding single human-single robot collaborative scenarios, but few address multi-user multi-robot scenarios. To this end, this paper presents a multi-robot multi-operator architecture, where the users' awareness is enhanced through an augmented reality head-mounted display. A multi-robot, multi-user collaborative scenario is presented in a laboratory environment with two industrial robots. Besides being able to interact with both robots in the system, each user becomes more aware of the robot's workspace and its pre-defined trajectories. Furthermore, it presents how fiducial markers can help to establish the relation between the different coordinate frames.

2024

The Role of Robotics: Automation in Shoe Manufacturing

Autores
Dias, A; Petry, R; Rocha, F;

Publicação
MESA 2024 - 20th International Conference on Mechatronic, Embedded Systems and Applications, Proceedings

Abstract
Emerging from a rich heritage, the shoe manufacturing industry stands as one of the world’s most enduring and tradition-bound sectors. While renowned for their high-quality craftsmanship, countries like Portugal and Italy share the spotlight with those who focus on mass production methods. Regardless of their manufacturing model, both must adapt to the evolving competitive landscape by embracing innovative manufacturing techniques. Robotics has emerged as a transformative force within the shoe industry, offering a path towards enhanced working conditions for employees while simultaneously reducing reliance on manual labor and bolstering productivity. The main focus of this paper is the comprehensive literature review, which examines the advancements made by researchers in various stages of shoe production, including roughing, gluing, finishing, and lasting. This article sheds light on the industry’s response to modernization and efficiency imperatives, providing a thorough understanding of robotics in shoe manufacturing automation. A case study on the real implementation and simulation of a robotic cell for sole roughing is also presented. The results revealed that the robotic cell maintains the production cadence. ©2024 IEEE.

Teses
supervisionadas

2023

Drone vision and deep learning for infrastructure inspection

Autor
José Pedro dos Santos Rodrigues

Instituição
UP-FEUP

2023

Multiuser Human-Machine Interface through Augmented Reality

Autor
João Daniel Ferreira Peixoto

Instituição
UP-FEUP

2023

Virtual Reality Applied to Welder Training

Autor
MANUEL BENTO BARBOSA DO COUTO

Instituição
UP-FEUP

2023

Multi-Sensorial Simultaneous Localization and Mapping in Unmanned Aerial Vehicles

Autor
João Graça Martins

Instituição
UP-FEUP

2023

Evaluation of the influence and impacts of an augmented reality application as a tool to support production in the context of industry 4.0

Autor
Gabriel de Moura Costa

Instituição
UP-FEUP