Umbrella Meshes: Elastic Mechanisms for Freeform Shape Deployment

ACM Transactions on Graphics (Proceedings of SIGGRAPH), July 2022.
Yingying Ren* · Uday Kusupati* · Julian Panetta · Florin Isvoranu · Davide Pellis · Tian Chen · Mark Pauly
*joint first author (order determined by coin toss)

About

This repository contains the source code and data for the paper Umbrella Meshes: Elastic Mechanisms for Freeform Shape Deployment, published at SIGGRAPH 2022.

Getting Started

C++ Code Dependencies

The C++ code relies on boost and cholmod/umfpack. The design optimization part of the code also depend on the commercial optimization package knitro; these will be omitted from the build if knitro is not found.

macOS

You can install all the necessary dependencies except knitro on macOS with MacPorts:

# Build/version control tools, C++ code dependencies
sudo port install cmake boost suitesparse ninja glew
# Dependencies for jupyterlab/notebooks
sudo port install npm6
conda install python

Ubuntu 19.04

A few more packages need to be installed on a fresh Ubuntu 19.04 install:

# Build/version control tools
sudo apt install git cmake ninja-build
# Dependencies for C++ code
sudo apt install libboost-filesystem-dev libboost-system-dev libboost-program-options-dev libsuitesparse-dev
# LibIGL/GLFW dependencies
sudo apt install libgl1-mesa-dev libxrandr-dev libxinerama-dev libxcursor-dev libxi-dev
# Offscreen render dependencies
sudo apt install libglew-dev libpng-dev
# Dependencies (pybind11, jupyterlab/notebooks)
sudo apt install python3-pip npm
# Ubuntu 19.04 packages an older version of npm that is incompatible with its nodejs version...
sudo npm install npm@latest -g

Obtaining and Building

Clone this repository recursively so that its submodules are also downloaded:

git clone --recursive https://github.com/EPFL-LGG/UmbrellaMesh

Build the C++ code and its Python bindings using cmake and your favorite build system. For example, with ninja:

cd UmbrellaMesh
mkdir build && cd build
cmake .. -GNinja
ninja

Running the Jupyter Notebooks

The preferred way to interact with the code is in a Jupyter notebook, using the Python bindings. We highly recommend that you install the Python dependencies and JupyterLab itself in a virtual environment (e.g., with venv).

pip3 install wheel # Needed if installing in a virtual environment
pip3 install jupyterlab==3.3.4 ipykernel==5.5.5 ipywidgets==7.7.2 jupyterlab-widgets==1.1.1 # Use a slightly older version of ipykernel to avoid cluttering notebook with stdout content.
# If necessary, follow the instructions in the warnings to add the Python user
# bin directory (containing the 'jupyter' binary) to your PATH...

git clone https://github.com/jpanetta/pythreejs
cd pythreejs
pip3 install -e .
cd js
jupyter labextension install .

pip3 install matplotlib numpy scipy pytest

Launch Jupyter lab from the root python directory:

cd python
jupyter lab

There are four demos in python/live_demos. Try them out!

License and Citation

The code of Umbrella Meshes is license under MIT License. If you use parts of this code for your own research, please consider citing our paper:

@article{RKP2022umbrellameshes,
	author = {Ren, Yingying and Kusupati, Uday and Panetta, Julian and Isvoranu, Florin and Pellis, Davide and Chen, Tian and Pauly, Mark},
	title = {Umbrella Meshes: Elastic Mechanisms for Freeform Shape Deployment},
	year = {2022},
	issue_date = {July 2022},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	volume = {41},
	number = {4},
	issn = {0730-0301},
	url = {https://doi.org/10.1145/3528223.3530089},
	doi = {10.1145/3528223.3530089},
    journal = {Transactions on Graphics (Proceedings of SIGGRAPH)},
	month = {jul},
	articleno = {152},
	numpages = {15},
	keywords = {deployable structure, computational design, numerical optimization, fabrication, physics-based simulation}
}