Michele Gattullo

Dr. Michele Gattullo

Politecnico di Bari - DMMM
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 August 2020 in IEEE Transactions on Visualization and Computer Graphics
Verified
Journal Article
Closed access
MGMichele Gattullo
Michele Gattullo
AEAlessandro Evangelista
Alessandro Evangelista
Antonio E. UvaAntonio E. Uva
Antonio E. Uva
Michele FiorentinoMichele Fiorentino
Michele Fiorentino
JGJoseph L. Gabbard
Joseph L. Gabbard
Industrial Augmented Reality (iAR) has demonstrated its advantages to communicate technical information in the fields of maintenance, assembly, and training. However, literature is scattered among different visual assets (i.e., AR visual user interface elements associated with a real scene). In this work, we present a systematic literature review of visual assets used in these industrial fields. We searched five databases, initially finding 1757 papers. Then, we selected 122 iAR papers from 1997 to 2019 and extracted 348 visual assets. We propose a classification for visual assets according to (i) what is displayed, (ii) how it conveys information (frame of reference, color coding, animation), and, (iii) why it is used. Our review shows that product models, text and auxiliary models are, in order, the most common, with each most often used to support operating, checking and locating tasks respectively. Other visual assets are scarcely used. Product and auxiliary models are commonly rendered world-fixed, color coding is not used as often as expected, while animations are limited to product and auxiliary model. This survey provides a snapshot of over 20 years of literature in iAR, useful to understand established practices to orientate in iAR interface design and to present future research directions.

27 May 2013 in IEEE Transactions on Visualization and Computer Graphics
Verified
Journal Article
Closed access
SDSaverio Debernardis
Saverio Debernardis
Michele FiorentinoMichele Fiorentino
Michele Fiorentino
MGMichele Gattullo
Michele Gattullo
GMGiuseppe Monno
Giuseppe Monno
Antonio E. UvaAntonio E. Uva
Antonio E. Uva
Efficient text visualization in head-worn augmented reality (AR) displays is critical because it is sensitive to display technology, text style and color, ambient illumination and so on. The main problem for the developer is to know the optimal text style for the specific display and for applications where color coding must be strictly followed because it is regulated by laws or internal practices. In this work, we experimented the effects on readability of two head-worn devices (optical and video see-through), two backgrounds (light and dark), five colors (white, black, red, green, and blue), and two text styles (plain text and billboarded text). Font type and size were kept constant. We measured the performance of 15 subjects by collecting about 5,000 measurements using a specific test application and followed by qualitative interviews. Readability turned out to be quicker on the optical see-through device. For the video see-through device, background affects readability only in case of text without billboard. Finally, our tests suggest that a good combination for indoor augmented reality applications, regardless of device and background, could be white text and blue billboard, while a mandatory color should be displayed as billboard with a white text message.

30 November 2021 in The International Journal of Advanced Manufacturing Technology
Verified
Journal Article
Closed access
PDF file
ELEnricoandrea Laviola
Enricoandrea Laviola
MGMichele Gattullo
Michele Gattullo
Vito ManghisiVito Manghisi
Vito Manghisi
Michele FiorentinoMichele Fiorentino
Michele Fiorentino
Antonio E. UvaAntonio E. Uva
Antonio E. Uva

20 October 2022 in Computers in Industry
Verified
Journal Article
Closed access
ELEnricoandrea Laviola
Enricoandrea Laviola
MGMichele Gattullo
Michele Gattullo
AEAlessandro Evangelista
Alessandro Evangelista
MFMichele Fiorentino
Michele Fiorentino
AUAntonio Emmanuele Uva
Antonio Emmanuele Uva

1 February 2020 in Materials
Verified
Journal Article
Open access
PDF file
GPGianluca Percoco
Gianluca Percoco
Antonio E. UvaAntonio E. Uva
Antonio E. Uva
Michele FiorentinoMichele Fiorentino
Michele Fiorentino
MGMichele Gattullo
Michele Gattullo
Vito ManghisiVito Manghisi
Vito Manghisi
ABAntonio Boccaccio
Antonio Boccaccio
In spite of the rather large use of the fused deposition modeling (FDM) technique for the fabrication of scaffolds, no studies are reported in the literature that optimize the geometry of such scaffold types based on mechanobiological criteria. We implemented a mechanobiology-based optimization algorithm to determine the optimal distance between the strands in cylindrical scaffolds subjected to compression. The optimized scaffolds were then 3D printed with the FDM technique and successively measured. We found that the difference between the optimized distances and the average measured ones never exceeded 8.27% of the optimized distance. However, we found that large fabrication errors are made on the filament diameter when the filament diameter to be realized differs significantly with respect to the diameter of the nozzle utilized for the extrusion. This feasibility study demonstrated that the FDM technique is suitable to build accurate scaffold samples only in the cases where the strand diameter is close to the nozzle diameter. Conversely, when a large difference exists, large fabrication errors can be committed on the diameter of the filaments. In general, the scaffolds realized with the FDM technique were predicted to stimulate the formation of amounts of bone smaller than those that can be obtained with other regular beam-based scaffolds.

24 March 2022 in Computers
Verified
Journal Article
Open access
PDF file
MGMichele Gattullo
Michele Gattullo
ELEnricoandrea Laviola
Enricoandrea Laviola
ABAntonio Boccaccio
Antonio Boccaccio
AEAlessandro Evangelista
Alessandro Evangelista
Michele FiorentinoMichele Fiorentino
Michele Fiorentino
Antonio E. UvaAntonio E. Uva
Antonio E. Uva
In this work, we propose a Mixed Reality (MR) application to support laboratory lectures in STEM distance education. It was designed following a methodology extendable to diverse STEM laboratory lectures. We formulated this methodology considering the main issues found in the literature that limit MR’s use in education. Thus, the main design features of the resulting MR application are students’ and teachers’ involvement, use of not distracting graphics, integration of traditional didactic material, and easy scalability to new learning activities. In this work, we present how we applied the design methodology and used the framework for the case study of an engineering course to support students in understanding drawings of complex machines without being physically in the laboratory. We finally evaluated the usability and cognitive load of the implemented MR application through two user studies, involving, respectively, 48 and 36 students. The results reveal that the usability of our application is “excellent” (mean SUS score 84.7), and it is not influenced by familiarity with Mixed Reality and distance education tools. Furthermore, the cognitive load is medium (mean NASA TLX score below 29) for all four learning tasks that students can accomplish through the MR application.