24/7 Space News
AI-driven tool makes it easy to personalize 3D-printable models
illustration only
AI-driven tool makes it easy to personalize 3D-printable models
by Adam Zewe for MIT News
Boston MA (SPX) Sep 18, 2023

As 3D printers have become cheaper and more widely accessible, a rapidly growing community of novice makers are fabricating their own objects. To do this, many of these amateur artisans access free, open-source repositories of user-generated 3D models that they download and fabricate on their 3D printer.

But adding custom design elements to these models poses a steep challenge for many makers, since it requires the use of complex and expensive computer-aided design (CAD) software, and is especially difficult if the original representation of the model is not available online. Plus, even if a user is able to add personalized elements to an object, ensuring those customizations don't hurt the object's functionality requires an additional level of domain expertise that many novice makers lack.

To help makers overcome these challenges, MIT researchers developed a generative-AI-driven tool that enables the user to add custom design elements to 3D models without compromising the functionality of the fabricated objects. A designer could utilize this tool, called Style2Fab, to personalize 3D models of objects using only natural language prompts to describe their desired design. The user could then fabricate the objects with a 3D printer.

"For someone with less experience, the essential problem they faced has been: Now that they have downloaded a model, as soon as they want to make any changes to it, they are at a loss and don't know what to do. Style2Fab would make it very easy to stylize and print a 3D model, but also experiment and learn while doing it," says Faraz Faruqi, a computer science graduate student and lead author of a paper introducing Style2Fab.

Style2Fab is driven by deep-learning algorithms that automatically partition the model into aesthetic and functional segments, streamlining the design process.

In addition to empowering novice designers and making 3D printing more accessible, Style2Fab could also be utilized in the emerging area of medical making. Research has shown that considering both the aesthetic and functional features of an assistive device increases the likelihood a patient will use it, but clinicians and patients may not have the expertise to personalize 3D-printable models.

With Style2Fab, a user could customize the appearance of a thumb splint so it blends in with her clothing without altering the functionality of the medical device, for instance. Providing a user-friendly tool for the growing area of DIY assistive technology was a major motivation for this work, adds Faruqi.

He wrote the paper with his advisor, co-senior author Stefanie Mueller, an associate professor in the MIT departments of Electrical Engineering and Computer Science and Mechanical Engineering, and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) who leads the HCI Engineering Group; co-senior author Megan Hofmann, assistant professor at the Khoury College of Computer Sciences at Northeastern University; as well as other members and former members of the group. The research will be presented at the ACM Symposium on User Interface Software and Technology.

Focusing on functionality
Online repositories, such as Thingiverse, allow individuals to upload user-created, open-source digital design files of objects that others can download and fabricate with a 3D printer.

Faruqi and his collaborators began this project by studying the objects available in these huge repositories to better understand the functionalities that exist within various 3D models. This would give them a better idea of how to use AI to segment models into functional and aesthetic components, he says.

"We quickly saw that the purpose of a 3D model is very context dependent, like a vase that could be sitting flat on a table or hung from the ceiling with string. So it can't just be an AI that decides which part of the object is functional. We need a human in the loop," he says.

Drawing on that assessment, they defined two functionalities: external functionality, which involves parts of the model that interact with the outside world, and internal functionality, which involves parts of the model that need to mesh together after fabrication.

A stylization tool would need to preserve the geometry of externally and internally functional segments while enabling customization of nonfunctional, aesthetic segments.

But to do this, Style2Fab has to figure out which parts of a 3D model are functional. Using machine learning, the system analyzes the model's topology to track the frequency of changes in geometry, such as curves or angles where two planes connect. Based on this, it divides the model into a certain number of segments.

Then, Style2Fab compares those segments to a dataset the researchers created which contains 294 models of 3D objects, with the segments of each model annotated with functional or aesthetic labels. If a segment closely matches one of those pieces, it is marked functional.

"But it is a really hard problem to classify segments just based on geometry, due to the huge variations in models that have been shared. So these segments are an initial set of recommendations that are shown to the user, who can very easily change the classification of any segment to aesthetic or functional," he explains.

Human in the loop
Once the user accepts the segmentation, they enter a natural language prompt describing their desired design elements, such as "a rough, multicolor Chinoiserie planter" or a phone case "in the style of Moroccan art." An AI system, known as Text2Mesh, then tries to figure out what a 3D model would look like that meets the user's criteria.

It manipulates the aesthetic segments of the model in Style2Fab, adding texture and color or adjusting shape, to make it look as similar as possible. But the functional segments are off-limits.

The researchers wrapped all these elements into the back-end of a user interface that automatically segments and then stylizes a model based on a few clicks and inputs from the user.

They conducted a study with makers who had a wide variety of experience levels with 3D modeling and found that Style2Fab was useful in different ways based on a maker's expertise. Novice users were able to understand and use the interface to stylize designs, but it also provided a fertile ground for experimentation with a low barrier to entry.

For experienced users, Style2Fab helped quicken their workflows. Also, using some of its advanced options gave them more fine-grained control over stylizations.

Moving forward, Faruqi and his collaborators want to extend Style2Fab so the system offers fine-grained control over physical properties as well as geometry. For instance, altering the shape of an object may change how much force it can bear, which could cause it to fail when fabricated. In addition, they want to enhance Style2Fab so a user could generate their own custom 3D models from scratch within the system. The researchers are also collaborating with Google on a follow-up project.

This research was supported by the MIT-Google Program for Computing Innovation and used facilities provided by the MIT Center for Bits and Atoms.

Research Report:"Style2Fab: Functionality-Aware Segmentation for Fabricating Personalized 3D Models with Generative AI"

Related Links
Computer Science and Artificial Intelligence Laboratory
Space Technology News - Applications and Research

Subscribe Free To Our Daily Newsletters

The following news reports may link to other Space Media Network websites.
Invisible tagging system enhances 3D object tracking
Boston MA (SPX) Aug 15, 2023
Stop me if you've seen this before: a black and white pixelated square in lieu of a physical menu at a restaurant. QR codes are seemingly ubiquitous in everyday life. Whether you see one on a coupon at the grocery store, a flyer on a bulletin board, or the wall at a museum exhibit, each code contains embedded data. Unfortunately, QR codes in physical spaces are sometimes replaced or tampered with to trick you into giving away your data to unwanted parties - a seemingly harmless set of pixels could ... read more

NASA joins the still controversial search for UFOs

US astronaut sets record for stint in space

Kombucha: Ally for Moon and Mars

Virgin Galactic notches fourth spaceflight in four months

Musk biography describes troubled tycoon driven by demons

Marcus Wandt will fly to International Space Station on third Axiom Space mission

SpaceX launches 22 Starlink satellites in 65th mission of 2023

The Vostochny cosmodrome: symbol of Moscow's struggling space sector

Sols 3948-3949: A Rocky Road, or Two!

Another Martian Weekend" Sols 3943-3945

Sols 3936-3939: Double the Fun

China publishes new datasets obtained by Mars, lunar probes

Tianzhou 5 spacecraft burns up on Earth reentry

Crew of Shenzhou XV mission honored for six-month space odyssey

China solicits names for manned lunar exploration vehicles

From rice to quantum gas: China's targets pioneering space research

Intelsat Inflight Connectivity expanded to all Airbus aircraft

Intelsat Adds European Capacity with Telespazio's Fucino Space Centre in Italy

Germany blocks full Chinese takeover of satellite startup

Telesat, SpaceX announce agreement to launch satellites

Gold and mercury, not books, for Venezuela's child miners

AI-driven tool makes it easy to personalize 3D-printable models

AWS ties up with ISRO and IN-SPACe to advance India's space capabilities with cloud technologies

Apple to update iPhone 12 in France over radiation

On the road to spotting alien life

Alleged bodies of 'non-human beings' shown in Mexican Congress

Webb discovers methane, carbon dioxide in atmosphere of K2-18 b

Scientists detect and validate the longest-period exoplanet found with TESS

Possible existence of Earth-like planet predicted in Outskirts of Solar System

SwRI will lead Hubble, Webb observations of Io, Jupiter's volcanic moon

In the service of planetary science, astrophysics and heliophysics

Mysterious Neptune dark spot detected from Earth for the first time

Subscribe Free To Our Daily Newsletters


The content herein, unless otherwise known to be public domain, are Copyright 1995-2023 - Space Media Network. All websites are published in Australia and are solely subject to Australian law and governed by Fair Use principals for news reporting and research purposes. AFP, UPI and IANS news wire stories are copyright Agence France-Presse, United Press International and Indo-Asia News Service. ESA news reports are copyright European Space Agency. All NASA sourced material is public domain. Additional copyrights may apply in whole or part to other bona fide parties. All articles labeled "by Staff Writers" include reports supplied to Space Media Network by industry news wires, PR agencies, corporate press officers and the like. Such articles are individually curated and edited by Space Media Network staff on the basis of the report's information value to our industry and professional readership. Advertising does not imply endorsement, agreement or approval of any opinions, statements or information provided by Space Media Network on any Web page published or hosted by Space Media Network. General Data Protection Regulation (GDPR) Statement Our advertisers use various cookies and the like to deliver the best ad banner available at one time. All network advertising suppliers have GDPR policies (Legitimate Interest) that conform with EU regulations for data collection. By using our websites you consent to cookie based advertising. If you do not agree with this then you must stop using the websites from May 25, 2018. Privacy Statement. Additional information can be found here at About Us.