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2018
Journal article
Open Access
Fabrication oriented shape decomposition using polycube mapping
Fanni F. A., Cherchi G., Muntoni A., Tola A., Scateni R.
In recent years, fabrication technologies have developed at a breakneck pace. However, some limitations on shape and dimension still apply both to additive and subtractive manufacturing, and one way to bypass them could be the partition of the object to build. We present here a novel algorithm, based on the polycube representation of the original shape, able to decompose any model into smaller parts simpler to fabricate. We first map the shape in a polycube and, then, split it to take advantage of the polycube partitioning. In this way, we obtain quite easily a partition of the model. In this work we also study and analyze pros and cons of this partitioning scheme for fabrication, when using both the additive and subtractive pipelines. Our proposed partitioning scheme is computationally light, and it produces high-grade results, especially when applied to models that we can map onto polycubes with a high compactness value.Source: Computers & graphics 77 (2018): 183–193. doi:10.1016/j.cag.2018.10.010
DOI: 10.1016/j.cag.2018.10.010
Metrics:
Fanni F. A., Cherchi G., Muntoni A., Tola A., Scateni R.
In recent years, fabrication technologies have developed at a breakneck pace. However, some limitations on shape and dimension still apply both to additive and subtractive manufacturing, and one way to bypass them could be the partition of the object to build. We present here a novel algorithm, based on the polycube representation of the original shape, able to decompose any model into smaller parts simpler to fabricate. We first map the shape in a polycube and, then, split it to take advantage of the polycube partitioning. In this way, we obtain quite easily a partition of the model. In this work we also study and analyze pros and cons of this partitioning scheme for fabrication, when using both the additive and subtractive pipelines. Our proposed partitioning scheme is computationally light, and it produces high-grade results, especially when applied to models that we can map onto polycubes with a high compactness value.Source: Computers & graphics 77 (2018): 183–193. doi:10.1016/j.cag.2018.10.010
DOI: 10.1016/j.cag.2018.10.010
Metrics:
See at:
Computers & Graphics 
| Computers & Graphics 
| www.sciencedirect.com | CNR ExploRA
2019
Conference article
Unknown
Split and mill: user assisted height-field block decomposition for fabrication
Muntoni A., Spano L. D., Scateni R.
We present here Split and Mill: an interactive system for the manual volume decomposition of free form shapes. Our primary purpose is to generate portions respecting the properties allowing to mill them with a 3-axis milling machine. We show that a manual decomposition is competitive with the automatic partitioning when the user is skilled enough. We, thus, think that our tool can be beneficial for the practitioners in the field, and we release it as free software.Source: Italian Chapter Conference 2019 - Smart Tools and Apps in computer Graphics, STAG 2019, pp. 61–70, Cagliari, Italy, November 14-15, 2019
DOI: 10.2312/stag.20191364
Metrics:
Muntoni A., Spano L. D., Scateni R.
We present here Split and Mill: an interactive system for the manual volume decomposition of free form shapes. Our primary purpose is to generate portions respecting the properties allowing to mill them with a 3-axis milling machine. We show that a manual decomposition is competitive with the automatic partitioning when the user is skilled enough. We, thus, think that our tool can be beneficial for the practitioners in the field, and we release it as free software.Source: Italian Chapter Conference 2019 - Smart Tools and Apps in computer Graphics, STAG 2019, pp. 61–70, Cagliari, Italy, November 14-15, 2019
DOI: 10.2312/stag.20191364
Metrics:
See at: diglib.eg.org | CNR ExploRA
2018
Conference article
Open Access
Simplification of shapes for fabrication with V-groove milling tools
Muntoni A., Scalas A., Nuvoli S., Scateni R.
We introduce here a pipeline for simplifying digital 3D shapes with the aim of fabricating them using 2D polygonal flat parts. Our method generates shapes that, once unfolded, can be fabricated with CNC milling machines using special tools called V-Grooves. These tools make V-shaped furrows at given angles depending on the shape of the used tool. Milling the edges of each flat facet simplifies the manual assembly that consists only in folding the facets at the desired angle between the adjacent facets. Our method generates simplified shapes where every dihedral angle between adjacent facets belongs to a restricted set, thus making the assembly process quicker and more straightforward. Firstly, our method automatically computes a simplification of the model, iterating local changes on a triangle mesh generated by applying the Marching Cubes algorithm on the original mesh. The user performs a second manual simplification using a tool that removes spurious facets. Finally, we use a simple unfolding algorithm which flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it with a sheet of rigid material.Source: STAG 2018 - Smart Tools and Applications in Graphics, Brescia, Italy, 18-19 October 2018
DOI: 10.2312/stag.20181293
Metrics:
Muntoni A., Scalas A., Nuvoli S., Scateni R.
We introduce here a pipeline for simplifying digital 3D shapes with the aim of fabricating them using 2D polygonal flat parts. Our method generates shapes that, once unfolded, can be fabricated with CNC milling machines using special tools called V-Grooves. These tools make V-shaped furrows at given angles depending on the shape of the used tool. Milling the edges of each flat facet simplifies the manual assembly that consists only in folding the facets at the desired angle between the adjacent facets. Our method generates simplified shapes where every dihedral angle between adjacent facets belongs to a restricted set, thus making the assembly process quicker and more straightforward. Firstly, our method automatically computes a simplification of the model, iterating local changes on a triangle mesh generated by applying the Marching Cubes algorithm on the original mesh. The user performs a second manual simplification using a tool that removes spurious facets. Finally, we use a simple unfolding algorithm which flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it with a sheet of rigid material.Source: STAG 2018 - Smart Tools and Applications in Graphics, Brescia, Italy, 18-19 October 2018
DOI: 10.2312/stag.20181293
Metrics:
See at:
diglib.eg.org | ISTI Repository | hdl.handle.net | CNR ExploRA
2021
Software
Unknown
MeshLab 2021.07
Muntoni A., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
Muntoni A., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
See at: CNR ExploRA | www.meshlab.net
2021
Software
Unknown
PyMeshLab 2021.07
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes.
Muntoni A., Cignoni P.
PyMeshLab is a Python library that interfaces to MeshLab, the popular open source application for editing and processing large 3D triangle meshes.
See at: CNR ExploRA | pymeshlab.readthedocs.io
2020
Software
Unknown
MeshLab 2020.12
Muntoni A., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
Muntoni A., Cignoni P.
MeshLab is an open source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes.
See at: CNR ExploRA | www.meshlab.net
2019
Journal article
Open Access
Mill and fold: shape simplification for fabrication
Muntoni A., Nuvoli S., Scalas A., Tola A., Malomo L., Scateni R.
We introduce a pipeline for simplifying digital 3D shapes and fabricate them using 2D polygonal flat parts. Our method generates shapes that, once unfolded, can be fabricated with CNC milling machines using special tools called V-Grooves. These tools create V-shaped furrows at given angles depending on the shape of the used tool. Milling the edges of each flat facet simplifies the manual assembly, which consists only in folding adjacent facets at a constrained angle. Our method generates simplified shapes where every dihedral angle between adjacent facets belongs to a restricted set, thus making the assembly process quicker and more straightforward. Firstly, our method automatically computes a simplified version of the input model, using the marching cubes algorithm on the original mesh and iteratively performing local changes on the resulting triangle mesh. The user can then perform an additional manual simplification to remove unwanted facets. Finally, an unfolding algorithm, which takes into account the thickness of the material, flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it from a sheet of rigid material.Source: Computers & graphics 80 (2019): 17–28. doi:10.1016/j.cag.2019.03.003
DOI: 10.1016/j.cag.2019.03.003
Metrics:
Muntoni A., Nuvoli S., Scalas A., Tola A., Malomo L., Scateni R.
We introduce a pipeline for simplifying digital 3D shapes and fabricate them using 2D polygonal flat parts. Our method generates shapes that, once unfolded, can be fabricated with CNC milling machines using special tools called V-Grooves. These tools create V-shaped furrows at given angles depending on the shape of the used tool. Milling the edges of each flat facet simplifies the manual assembly, which consists only in folding adjacent facets at a constrained angle. Our method generates simplified shapes where every dihedral angle between adjacent facets belongs to a restricted set, thus making the assembly process quicker and more straightforward. Firstly, our method automatically computes a simplified version of the input model, using the marching cubes algorithm on the original mesh and iteratively performing local changes on the resulting triangle mesh. The user can then perform an additional manual simplification to remove unwanted facets. Finally, an unfolding algorithm, which takes into account the thickness of the material, flattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it from a sheet of rigid material.Source: Computers & graphics 80 (2019): 17–28. doi:10.1016/j.cag.2019.03.003
DOI: 10.1016/j.cag.2019.03.003
Metrics:
See at:
ISTI Repository | Computers & Graphics | www.sciencedirect.com | CNR ExploRA
2021
Journal article
Open Access
TagLab: AI-assisted annotation for the fast and accurate semantic segmentation of coral reef orthoimages
Pavoni G., Corsini M., Ponchio F., Muntoni A., Edwards C., Pedersen N., Sandin S., Cignoni P.
Semantic segmentation is a widespread image analysis task; in some applications, it requires such high accuracy that it still has to be done manually, taking a long time. Deep learning-based approaches can significantly reduce such times, but current automated solutions may produce results below expert standards. We propose agLab, an interactive tool for the rapid labelling and analysis of orthoimages that speeds up semantic segmentation. TagLab follows a human-centered artificial intelligence approach that, by integrating multiple degrees of automation, empowers human capabilities. We evaluated TagLab's efficiency in annotation time and accuracy through a user study based on a highly challenging task: the semantic segmentation of coral communities in marine ecology. In the assisted labelling of corals, TagLab increased the annotation speed by approximately 90% for nonexpert annotators while preserving the labelling accuracy. Furthermore, human-machine interaction has improved the accuracy of fully automatic predictions by about 7% on average and by 14% when the model generalizes poorly. Considering the experience done through the user study, TagLab has been improved, and preliminary investigations suggest a further significant reduction in annotation times.Source: Journal of field robotics (2021). doi:10.1002/rob.22049
DOI: 10.1002/rob.22049
Metrics:
Pavoni G., Corsini M., Ponchio F., Muntoni A., Edwards C., Pedersen N., Sandin S., Cignoni P.
Semantic segmentation is a widespread image analysis task; in some applications, it requires such high accuracy that it still has to be done manually, taking a long time. Deep learning-based approaches can significantly reduce such times, but current automated solutions may produce results below expert standards. We propose agLab, an interactive tool for the rapid labelling and analysis of orthoimages that speeds up semantic segmentation. TagLab follows a human-centered artificial intelligence approach that, by integrating multiple degrees of automation, empowers human capabilities. We evaluated TagLab's efficiency in annotation time and accuracy through a user study based on a highly challenging task: the semantic segmentation of coral communities in marine ecology. In the assisted labelling of corals, TagLab increased the annotation speed by approximately 90% for nonexpert annotators while preserving the labelling accuracy. Furthermore, human-machine interaction has improved the accuracy of fully automatic predictions by about 7% on average and by 14% when the model generalizes poorly. Considering the experience done through the user study, TagLab has been improved, and preliminary investigations suggest a further significant reduction in annotation times.Source: Journal of field robotics (2021). doi:10.1002/rob.22049
DOI: 10.1002/rob.22049
Metrics:
See at:
onlinelibrary.wiley.com | ISTI Repository | CNR ExploRA
2021
Conference article
Open Access
TagLab: A human-centric AI system for interactive semantic segmentation
Pavoni G., Corsini M., Ponchio F., Muntoni A., Cignoni P.
Fully automatic semantic segmentation of highly specific semantic classes and complex shapes may not meet the accuracy standards demanded by scientists. In such cases, human-centered AI solutions, able to assist operators while preserving human control over complex tasks, are a good trade-off to speed up image labeling while maintaining high accuracy levels. TagLab is an open-source AI-assisted software for annotating large orthoimages which takes advantage of different degrees of automation; it speeds up image annotation from scratch through assisted tools, creates custom fully automatic semantic segmentation models, and, finally, allows the quick edits of automatic predictions. Since the orthoimages analysis applies to several scientific disciplines, TagLab has been designed with a flexible labeling pipeline. We report our results in two different scenarios, marine ecology, and architectural heritage.Source: Human Centered AI Workshop at NeurIPS 2021 - Thirty-fifth Conference on Neural Information Processing Systems, Online event, 13/12/2021
DOI: 10.48550/arxiv.2112.12702
Metrics:
Pavoni G., Corsini M., Ponchio F., Muntoni A., Cignoni P.
Fully automatic semantic segmentation of highly specific semantic classes and complex shapes may not meet the accuracy standards demanded by scientists. In such cases, human-centered AI solutions, able to assist operators while preserving human control over complex tasks, are a good trade-off to speed up image labeling while maintaining high accuracy levels. TagLab is an open-source AI-assisted software for annotating large orthoimages which takes advantage of different degrees of automation; it speeds up image annotation from scratch through assisted tools, creates custom fully automatic semantic segmentation models, and, finally, allows the quick edits of automatic predictions. Since the orthoimages analysis applies to several scientific disciplines, TagLab has been designed with a flexible labeling pipeline. We report our results in two different scenarios, marine ecology, and architectural heritage.Source: Human Centered AI Workshop at NeurIPS 2021 - Thirty-fifth Conference on Neural Information Processing Systems, Online event, 13/12/2021
DOI: 10.48550/arxiv.2112.12702
Metrics:
See at:
arXiv.org e-Print Archive | ISTI Repository | doi.org | CNR ExploRA
2022
Journal article
Open Access
Design and construction of a bending-active plywood structure: the Flexmaps Pavilion
Laccone F., Malomo L., Callieri M., Alderighi T., Muntoni A., Ponchio F., Pietroni N., Cignoni P.
Mesostructured patterns are a modern and efficient concept based on designing the geometry of structural material at the meso-scale to achieve desired mechanical performances. In the context of bending-active structures, such a concept can be used to control the flexibility of the panels forming a surface without changing the constituting material. These panels undergo a formation process of deformation by bending, and application of internal restraints. This paper describes a new constructional system, FlexMaps, that has initiated the adoption of bending-active mesostructures at the architectural scale. Here, these modules are in the form of four-arms spirals made of CNC-milled plywood and are designed to reach the desired target shape once assembled. All phases from the conceptual design to the fabrication are seamlessly linked within an automated workflow. To illustrate the potential of the system, the paper discusses the results of a demonstrator project entitled FlexMaps Pavilion (3.90x3.96x3.25 meters) that has been exhibited at the IASS Symposium in 2019 and more recently at the 2021 17th International Architecture Exhibition, La Biennale di Venezia. The structural response is investigated through a detailed structural analysis, and the long-term behavior is assessed through a photogrammetric survey.Source: Journal of the International Association for Shell and Spatial Structures 63 (2022): 98–114. doi:10.20898/j.iass.2022.007
DOI: 10.20898/j.iass.2022.007
Metrics:
Laccone F., Malomo L., Callieri M., Alderighi T., Muntoni A., Ponchio F., Pietroni N., Cignoni P.
Mesostructured patterns are a modern and efficient concept based on designing the geometry of structural material at the meso-scale to achieve desired mechanical performances. In the context of bending-active structures, such a concept can be used to control the flexibility of the panels forming a surface without changing the constituting material. These panels undergo a formation process of deformation by bending, and application of internal restraints. This paper describes a new constructional system, FlexMaps, that has initiated the adoption of bending-active mesostructures at the architectural scale. Here, these modules are in the form of four-arms spirals made of CNC-milled plywood and are designed to reach the desired target shape once assembled. All phases from the conceptual design to the fabrication are seamlessly linked within an automated workflow. To illustrate the potential of the system, the paper discusses the results of a demonstrator project entitled FlexMaps Pavilion (3.90x3.96x3.25 meters) that has been exhibited at the IASS Symposium in 2019 and more recently at the 2021 17th International Architecture Exhibition, La Biennale di Venezia. The structural response is investigated through a detailed structural analysis, and the long-term behavior is assessed through a photogrammetric survey.Source: Journal of the International Association for Shell and Spatial Structures 63 (2022): 98–114. doi:10.20898/j.iass.2022.007
DOI: 10.20898/j.iass.2022.007
Metrics:
See at:
ISTI Repository | CNR ExploRA