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2021 Journal article Restricted

Volume decomposition for two-piece rigid casting
Alderighi T., Malomo L., Bickel B., Cignoni P., Pietroni N.
We introduce a novel technique to automatically decompose an input object's volume into a set of parts that can be represented by two opposite height fields. Such decomposition enables the manufacturing of individual parts using two-piece reusable rigid molds. Our decomposition strategy relies on a new energy formulation that utilizes a pre-computed signal on the mesh volume representing the accessibility for a predefined set of extraction directions. Thanks to this novel formulation, our method allows for efficient optimization of a fabrication-aware partitioning of volumes in a completely automatic way. We demonstrate the efficacy of our approach by generating valid volume partitionings for a wide range of complex objects and physically reproducing several of them.Source: ACM transactions on graphics 40 (2021). doi:10.1145/3478513.3480555
DOI: 10.1145/3478513.3480555
Project(s): MATERIALIZABLE via OpenAIRE

See at: CNR ExploRA Restricted


2020 Journal article Open Access OPEN

Optimizing object decomposition to reduce visual artifacts in 3D printing
Filoscia I., Alderighi T., Giorgi D., Malomo L., Callieri M., Cignoni P.
We propose a method for the automatic segmentation of 3D objects into parts which can be individually 3D printed and then reassembled by preserving the visual quality of the final object. Our technique focuses on minimizing the surface affected by supports, decomposing the object into multiple parts whose printing orientation is automatically chosen. The segmentation reduces the visual impact on the fabricated model producing non-planar cuts that adapt to the object shape. This is performed by solving an optimization problem that balances the effects of supports and cuts, while trying to place both in occluded regions of the object surface. To assess the practical impact of the solution, we show a number of segmented, 3D printed and reassembled objects.Source: Computer graphics forum (Print) 39 (2020): 423–434. doi:10.1111/cgf.13941
DOI: 10.1111/cgf.13941
Project(s): EVOCATION via OpenAIRE

See at: onlinelibrary.wiley.com Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted | Computer Graphics Forum Restricted


2019 Journal article Open Access OPEN

Volume-aware design of composite molds
Alderighi T., Malomo L., Giorgi D., Bickel B., Cignoni P. Pietroni N.
We propose a novel technique for the automatic design of molds to cast highly complex shapes. The technique generates composite, two-piece molds. Each mold piece is made up of a hard plastic shell and a flexible silicone part. Thanks to the thin, soft, and smartly shaped silicone part, which is kept in place by a hard plastic shell, we can cast objects of unprecedented complexity. An innovative algorithm based on a volumetric analysis defines the layout of the internal cuts in the silicone mold part. Our approach can robustly handle thin protruding features and intertwined topologies that have caused previous methods to fail. We compare our results with state of the art techniques, and we demonstrate the casting of shapes with extremely complex geometry.Source: ACM transactions on graphics 38 (2019). doi:10.1145/3306346.3322981
DOI: 10.1145/3306346.3322981
Project(s): EVOCATION via OpenAIRE, EMOTIVE via OpenAIRE, MATERIALIZABLE via OpenAIRE

See at: ISTI Repository Open Access | ACM Transactions on Graphics Open Access | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | CNR ExploRA Restricted | ACM Transactions on Graphics Restricted


2019 Report Restricted

A survey on 3D shape segmentation with focus on digital fabrication
Filoscia I., Alderighi T. Cignoni P., Giorgi D., Malomo L.
Segmenting 3D objects into parts is fundamental to a number of applications in computer graphics, including parametrization, texture mapping, shape matching, morphing, multi-resolution modeling, mesh editing, compression and animation [22]. Broadly speaking, shape segmentation techniques can be divided into geometry-based and semantics-based techniques. Geometry-based segmentations aim to partition the object into parts which have well-defined geometric properties such as size, curvature, or distance to a fitting primitive like a plane. Semantics-based segmentations, in turn, aim at identifying parts which are either visually relevant or meaningful in a given context, such as functional parts on mechanical objects or body parts on human models. Recently, 3D segmentation also drawn attention as a tool for efficient fabrication. The decomposition of objects into parts, indeed, helps solving different issues related to fabrication, such as height field constraints, volume constraints and need for supporting structures. In this work we present a complete survey of segmentation techniques, also highlighting their strengths and weaknesses. Our aim is to produce a handy overview to people who want to approach the problem of segmentation, especially if they want to apply it to digital fabrication.Source: ISTI Technical reports, 2019

See at: CNR ExploRA Restricted


2019 Report Restricted

A novel segmentation algorithm for support-free 3D printing
Filoscia I., Alderighi T., Cignoni P., Giorgi D., Malomo L.
Digital fabrication, and 3D printing in particular, are growing important in a variety of fields, from industry to medicine, from cultural heritage to art, as often they are more rapid and cheaper than traditional manufacturing techniques. In this context, our aim is to make it easier for people to print high-quality objects at home, even of complex shape, by incorporating into software some of the professional skills that are needed to fully exploit the potential of 3D printing A major limitation of FDM printers is that the material must be supported when it is deposited: bridge-like structures or hanging features, which are not supported by other object parts, often need additional support structures. Indeed, most printers can produce overhangs, but only up to a certain tolerance angle, usually in-between 30 and 60 degrees. To solve this problem, additional columns of material are built to support the parts in overhang. These supports need to be removed in a postprocessing step, which may cause imperfections on the surface, or even break thin parts. A possible solution, which we adopt in this work, is to segment the object into smaller parts which can be printed individually with no or minimal need for supports. The main drawback is that the decomposition introduces cuts on the object surface, in correspondence of the boundaries between parts. Such cuts can be as visually disturbing as the imperfections due to the removal of supports, or even more. Therefore, given a 3D mesh representing the input object, our aim is to develop a segmentation technique to partition the mesh into a small number of simpler parts, each of which can be printed with no or minimal support, and such that the boundaries between the parts (i.e., where the cuts in the object surface will be) affect the appearance of the printed model as little as possible. We pose the segmentation problem as a multi-labeling problem solved via functional minimization. In our formulation, the data points will be mesh elements (either faces or clusters of faces), and the labels will be potential printing directions. We will define an objective function that takes into account the area of supported regions and support footings, as well as the visual impact of the cuts, in terms of both their length and location on the surface. We formulate this multi-labeling problem as an Integer Linear Program (ILP), which can be solved using standard optimization packages such as Gurobi.Source: ISTI Technical reports, 2019

See at: CNR ExploRA Restricted


2019 Contribution to conference Open Access OPEN

Computational fabrication of macromolecules to enhance perception and understanding of biological mechanisms
Alderighi T., Giorgi D., Malomo L., Cignoni P., Zoppè M.
We propose a fabrication technique for the fast and cheap production of 3D replicas of proteins. We leverage silicone casting with rigid molds, to produce flexible models which can be safely extracted from the mold, and easily manipulated to simulate the biological interaction mechanisms between proteins. We believe that tangible models can be useful in education as well as in laboratory settings, and that they will ease the understanding of fundamental principles of macromolecular organization.Source: Smart Tools and Applications in Graphics (STAG) 2019, pp. 103–104, Cagliari, Italy, 14-15/11/2019
DOI: 10.2312/stag.20191369

See at: diglib.eg.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2018 Journal article Open Access OPEN

Metamolds: computational design of silicone molds
Alderighi T., Malomo L., Giorgi D., Pietroni N., Bickel B., Cignoni P.
We propose a new method for fabricating digital objects through reusable silicone molds. Molds are generated by casting liquid silicone into custom 3D printed containers called metamolds. Metamolds automatically define the cuts that are needed to extract the cast object from the silicone mold. The shape of metamolds is designed through a novel segmentation technique, which takes into account both geometric and topological constraints involved in the process of mold casting. Our technique is simple, does not require changing the shape or topology of the input objects, and only requires off-the-shelf materials and technologies. We successfully tested our method on a set of challenging examples with complex shapes and rich geometric detailSource: ACM transactions on graphics 37 (2018): 136:1–136:13. doi:10.1145/3197517.3201381
DOI: 10.1145/3197517.3201381
Project(s): EMOTIVE via OpenAIRE

See at: ISTI Repository Open Access | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted | CNR ExploRA Restricted | ACM Transactions on Graphics Restricted | ACM Transactions on Graphics Restricted