29 citations · 57 across the 10 of their papers we have counts for
12 papers
How Can Large Language Models Help Humans in Design and Manufacturing?
Liane Makatura, Michael Foshey, Bohan Wang +15
The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the…
Zero-shot CAD Program Re-Parameterization for Interactive Manipulation
Milin Kodnongbua, Benjamin T. Jones, Maaz Bin Safeer Ahmad +2
Parametric CAD models encode entire families of shapes that should, in principle, be easy for designers to explore. However, in practice, parametric CAD models can be difficult to…
Computational Design of Passive Grippers
Milin Kodnongbua, Ian Good Yu Lou, Jeffrey Lipton +1
This work proposes a novel generative design tool for passive grippers -- robot end effectors that have no additional actuation and instead leverage the existing degrees of freedom…
B-rep Matching for Collaborating Across CAD Systems
Benjamin Jones, James Noeckel, Milin Kodnongbua +2
Large Computer-Aided Design (CAD) projects usually require collaboration across many different CAD systems as well as applications that interoperate with them for manufacturing, vi…
Neurosymbolic Models for Computer Graphics
Daniel Ritchie, Paul Guerrero, R. Kenny Jones +4
Procedural models (i.e. symbolic programs that output visual data) are a historically-popular method for representing graphics content: vegetation, buildings, textures, etc. They o…
Self-Supervised Representation Learning for CAD
Benjamin T. Jones, Michael Hu, Vladimir G. Kim +1
The design of man-made objects is dominated by computer aided design (CAD) tools. Assisting design with data-driven machine learning methods is hampered by lack of labeled data in…
Mates2Motion: Learning How Mechanical CAD Assemblies Work
James Noeckel, Benjamin T. Jones, Karl Willis +2
We describe our work on inferring the degrees of freedom between mated parts in mechanical assemblies using deep learning on CAD representations. We train our model using a large d…
Differentiable 3D CAD Programs for Bidirectional Editing
Dan Cascaval, Mira Shalah, Phillip Quinn +3
Modern CAD tools represent 3D designs not only as geometry, but also as a program composed of geometric operations, each of which depends on a set of parameters. Program representa…
Rewrite Rule Inference Using Equality Saturation
Chandrakana Nandi, Max Willsey, Amy Zhu +6
Many compilers, synthesizers, and theorem provers rely on rewrite rules to simplify expressions or prove equivalences. Developing rewrite rules can be difficult: rules may be subtl…
Co-Optimization of Design and Fabrication Plans for Carpentry
Haisen Zhao, Max Willsey, Amy Zhu +4
Past work on optimizing fabrication plans given a carpentry design can provide Pareto-optimal plans trading off between material waste, fabrication time, precision, and other consi…
Fabrication-Aware Reverse Engineering for Carpentry
James Noeckel, Haisen Zhao, Brian Curless +1
We propose a novel method to generate fabrication blueprints from images of carpentered items. While 3D reconstruction from images is a well-studied problem, typical approaches pro…
AutoMate: A Dataset and Learning Approach for Automatic Mating of CAD Assemblies
Benjamin Jones, Dalton Hildreth, Duowen Chen +3
Assembly modeling is a core task of computer aided design (CAD), comprising around one third of the work in a CAD workflow. Optimizing this process therefore represents a huge oppo…