This is the open-source reference implementation of the SIGGRAPH 2021 paper Intersection-free Rigid Body Dynamics.

Overview

Rigid IPC

Build License

Robust, intersection-free, simulations of rigid bodies.

This is the open-source reference implementation of the SIGGRAPH 2021 paper Intersection-free Rigid Body Dynamics.

Files

  • src/: source code
  • cmake/ and CMakeLists.txt: CMake files
  • fixtures/: input scripts to rerun all examples in our paper
  • meshes/: input meshes used by the fixtures
  • tests/: unit-tests
  • tools/: Python and Bash scripts for generating and processing results
  • comparisons/: files used in comparisons with other rigid body simulators
  • python/: Python binding files
  • notebooks/: Jupyter notebooks

Build

To build the project, use the following commands from the root directory of the project:

mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make -j4

Dependencies

All dependancies are downloaded through CMake depending on the build options. The following libraries are used in this project:

  • IPC Toolkit: common IPC functions
  • Eigen: linear algebra
  • libigl: basic geometry functions, predicates, and viewer
  • TBB: parallelization
  • Tight Inclusion CCD: correct (conservative) continuous collision detection between triangle meshes in 3D
  • spdlog: logging information
  • filib: interval arithmetic
  • Niels Lohmann's JSON: parsing input JSON scenes
  • tinygltf: exporting simulation animation to GLTF format
  • finite-diff: finite difference comparisons
    • Only used by the unit tests and when RIGID_IPC_WITH_DERIVATIVE_CHECK=ON

Optional

Scenes

We take as input a single JSON file that specifies the mesh and initial conditions for each body. The fixtures directory contains example scenes.

Python Bindings

We expose some functionality of Rigid IPC through Python. This is still in development and lacks the ability to script many features available in the full simulator.

To build the Python bindings use the setup.py script:

python setup.py install
Comments
  • cmake fails on Linux Mint 19.3

    cmake fails on Linux Mint 19.3

    Here is what I typed:

    $ mkdir build
    $ cd build
    $ cmake -DCMAKE_BUILD_TYPE=Release ..
    -- GCC >= 4.9 detected, enabling colored diagnostics
    -- Third-party: creating target 'Eigen3::Eigen'
    -- Third-party: creating target 'igl::core'
    -- Creating target: igl::core (igl)
    -- Creating target: igl::opengl (igl_opengl)
    -- Creating target: igl::opengl_glfw (igl_opengl_glfw)
    -- Using X11 for window creation
    -- Creating target: igl::opengl_glfw_imgui (igl_opengl_glfw_imgui)
    -- Creating target: igl::png (igl_png)
    -- Creating target: igl::predicates (igl_predicates)
    -- Third-party: creating target 'nlohmann::json'
    -- Third-party: creating target 'spdlog::spdlog'
    -- Build spdlog: 1.9.0
    -- Build type: Release
    -- Generating install
    -- Third-party: creating target 'finitediff::finitediff'
    -- Third-party: creating targets 'Boost::boost'
    -- Fetching Boost
    -- Fetching Boost - done
    -- Boost found: 1.71.0 /home/glenn/src/github.com/ipc-sim/rigid-ipc/build/_deps/boost-src
    -- Found the following ICU libraries:
    --   uc (required)
    --   dt (required)
    --   i18n (required)
    -- Third-party: creating target 'TBB::tbb'
    -- Third-party: creating target 'tight_inclusion::tight_inclusion'
    -- Tight-Inclusion CCD bottom-level project
    -- GCC >= 4.9 detected, enabling colored diagnostics
    -- Searching for AVX...
    -- Using CPU native flags for AVX optimization:  -march=native
    --   Found AVX 2.0 extensions, using flags:  -march=native -mavx2 -mno-avx512f -mno-avx512pf -mno-avx512er -mno-avx512cd
    -- Using Double Precision Floating Points
    -- Third-party: creating target 'PolyFEM::polysolve'
    [ 11%] Performing download step (git clone) for 'polysolve-populate'
    Cloning into 'polysolve-src'...
    fatal: reference is not a tree: a94e9b8ed8302d4b479533c67419f31addb1e987
    CMake Error at polysolve-subbuild/polysolve-populate-prefix/tmp/polysolve-populate-gitclone.cmake:40 (message):
      Failed to checkout tag: 'a94e9b8ed8302d4b479533c67419f31addb1e987'
    
    
    CMakeFiles/polysolve-populate.dir/build.make:110: recipe for target 'polysolve-populate-prefix/src/polysolve-populate-stamp/polysolve-populate-download' failed
    make[2]: *** [polysolve-populate-prefix/src/polysolve-populate-stamp/polysolve-populate-download] Error 1
    CMakeFiles/Makefile2:94: recipe for target 'CMakeFiles/polysolve-populate.dir/all' failed
    make[1]: *** [CMakeFiles/polysolve-populate.dir/all] Error 2
    Makefile:102: recipe for target 'all' failed
    make: *** [all] Error 2
    
    CMake Error at /usr/local/cmake-3.18.2-Linux-x86_64/share/cmake-3.18/Modules/FetchContent.cmake:987 (message):
      Build step for polysolve failed: 2
    Call Stack (most recent call first):
      /usr/local/cmake-3.18.2-Linux-x86_64/share/cmake-3.18/Modules/FetchContent.cmake:1082:EVAL:2 (__FetchContent_directPopulate)
      /usr/local/cmake-3.18.2-Linux-x86_64/share/cmake-3.18/Modules/FetchContent.cmake:1082 (cmake_language)
      /usr/local/cmake-3.18.2-Linux-x86_64/share/cmake-3.18/Modules/FetchContent.cmake:1125 (FetchContent_Populate)
      cmake/recipes/polysolve.cmake:14 (FetchContent_MakeAvailable)
      CMakeLists.txt:225 (include)
    
    
    -- Configuring incomplete, errors occurred!
    See also "/home/glenn/src/github.com/ipc-sim/rigid-ipc/build/CMakeFiles/CMakeOutput.log".
    See also "/home/glenn/src/github.com/ipc-sim/rigid-ipc/build/CMakeFiles/CMakeError.log".
    

    Any ideas how to fix this? It looks like a bad git reference in polysolve-src, possibly.

    Thank you!

    opened by gmlewis 6
  • Missing files or invalid fixture scripts?

    Missing files or invalid fixture scripts?

    I tried some of the examples in the "fixtures" directory, and the simulator works great! Nice work!

    However, I discovered that there are some examples that don't run either because their mesh files don't exist in the repo or because of some other problem.

    For example, this example is missing its meshes: https://github.com/ipc-sim/rigid-ipc/blob/main/fixtures/3D/mechanisms/expanding-lock-box.json#L11-L57

    This example says [2021-09-30 19:57:28.039] [error] Invalid Json file: https://github.com/ipc-sim/rigid-ipc/blob/main/fixtures/2D/compactor.json

    opened by gmlewis 3
  • Added TimeStepping (WIP)

    Added TimeStepping (WIP)

    Updated clang-format so long chains of parameters are shown one on each line (don't hate me)

    IO

    • Added rigid-body fixtures (NEW FORMAT!)
      • Added rigid-body reader
    • Added json/eigen helper to read/write matrices

    OPT

    • Added is_barrier method (and get/set epsilon) to CollisionConstraint so we don't need to pass the BarrierConstraint to the solver
      • Updated barrier constraint to use them
    • Added accessors on OptimizationProblem for barrier case
      • updated ad-hoc problem too since it was used on unit-tests

    PHYSICS

    • updated RigidBody class to

      • include theta: position is now length 3 (x, y, theta)
      • compute mass and moment of intertia (needed for forces)
      • added position of previous step
      • added differentiable world vertices, and flag to obtain the vertices of the current or previous step.
      • TODO: remove world_displacements, we should use world_vertices instead!
    • Added RigidBodyAssembler (to replace RigidBodyAssembler once finished)

      • init method only computes inmmutable information
      • other methods compute assembly on call

    SIMULATION

    • Added new main file for simulation
    • Added UISimSate and UIMenu for the simulation UI
    • TODO: merge with collision-debugging UI or add export of single problematic step
    opened by panchagil 1
  • Newton fix

    Newton fix

    I updated the Newton solver to fail to gradient descent if the line search fails. This helps the optimization make progress even when the Hessian is ill-conditioned. The next step after this pull request is merged is to add a quasi-Newton solver (e.g. BFGS).

    • Exposed initialization of barrier epsilon in the UI.
    • Separated line search into its own file.
    • Newton method now fails to gradient descent.
    opened by zfergus 1
  • Chain rule refactor

    Chain rule refactor

    Refactor structure of project. Now we have only 4 problems

    • Rigid Body Physics + Distance Barrier Constraint + Barrier Solver

    • Particles Physics + Distance Barrier Constraint + Barrier Solver

    • Rigid Body Physics + Volume Constraint + NCP Solver

    • Particles Physics + Volume Constraint + NCP Solver

    • Remove some base classes that were forcing us to write more functions than neccesary

      • Base OptimizationProblem is gone, now we have some interfaces for the different problems
      • Base CollisionConstraint remainds but implements few methods.
    • Removed exmplicit template instantiation and instead created .tpp files to keep template implementations

    opened by panchagil 0
  • Combined the distance barrier and CCD broad-phases

    Combined the distance barrier and CCD broad-phases

    • Exposed broad-phase in order to get the candidate collisions
    • Modified DistanceBarrier::detectCollisions to first build a common collision candidate set
    • Using this set run the narrow-phase of both the barrier and the CCD
    • TODO: Expose the ev_candidates as a member variable.
    • TODO: Add a is_collision_candidates_frozen flag to cause detectCollisions to not run the broad-phase again.
    opened by zfergus 0
  • Added BFGS and gradient descent solvers

    Added BFGS and gradient descent solvers

    • Added BFGS and GD to barrier solver as inner solvers
    • Needed to move some functionality out of NewtonSolver and into OptimizationSolvers
    • TODO: Move free_dof out of the OptimizationSolver and into the optimization problem with the eval_* functions using free_dof to remove elements.
    opened by zfergus 0
  • Added Rigid Body System Derivatives and  Rigid Body Problem

    Added Rigid Body System Derivatives and Rigid Body Problem

    • Added python notebook to get exact derivatives of RB transformation
    • Moved rigid body to its own file (out of rigid_body_system)
      • Added tests for RB gradient/hessian comparing with exact solutions
    • Added assembly of gradient and hessian on RB-System
      • Added test for RB-System comparing with exact solutions

    Added Rigid Body Problem

    • Added Rigid Body Problem to opt/
    • Implemented Functional, its gradient and hessian
      • tested against finite differences
    • Added tensor util to compute the multiplication of (1x2N) * (2N x 3B x 3B) used by the chain rule.
    opened by panchagil 0
  • Rigid body system

    Rigid body system

    • Moved rigid bodies to physics/ folder
      • added RigidBodySystem that keeps list of RB.
    • Moved solvers to solvers/ folder
    • Removed (a lot of)unused code
    opened by panchagil 0
  • Rigid bodies

    Rigid bodies

    Add UI features for controlling rigid bodies individually

    • Added gradient and hessian of compute_particle_displacements
      • This will be removed later it not used
    • Improved readability by using .homogeneous and .hnormalized
    • Edit buttons half width
    • Rigid body section to control the velocity of each body
    • State method to update the displacements and other fields from the rigid bodies
    opened by zfergus 0
  • Add menu to procedurally generate a chain of n links

    Add menu to procedurally generate a chain of n links

    The menu loads the one-link fixture file and duplicates the link n times. Each link has a scaled displacement, so all links have at least one contact.

    opened by zfergus 0
  • Unknown CMake command

    Unknown CMake command "rigid_ipc_download_project"

    Hi, I git clone the rigid-ipc, and use python build.py to compile the project.

    It gives this error: CMake Error at python/CMakeLists.txt:6 (rigid_ipc_download_project): Unknown CMake command "rigid_ipc_download_project". Call Stack (most recent call first): python/CMakeLists.txt:13 (rigid_ipc_download_pybind11)

    my cmake version is 3.16.3 os: ubuntu 20.04 python: miniconda with python 3.7

    BTW, I also tried with:

    mkdir build
    cd build
    cmake -DCMAKE_BUILD_TYPE=Release ..
    make
    

    This can make with no mistakes.

    I think something wrong with the python part? Any suggestions? Thanks!

    opened by WenqiangX 0
Releases(s2021)
Owner
Incremental Potential Contact code and related projects.
CVPR 2021 Challenge on Super-Resolution Space

Learning the Super-Resolution Space Challenge NTIRE 2021 at CVPR Learning the Super-Resolution Space challenge is held as a part of the 6th edition of

andreas 104 Oct 26, 2022
NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch

NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch, train it, collect statistics, and share it among the members of the community. It is not just a visual

HTM Community 93 Sep 30, 2022
CVPR 2021 Official Pytorch Code for UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training

UC2 UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training Mingyang Zhou, Luowei Zhou, Shuohang Wang, Yu Cheng, Linjie Li, Zhou Yu,

Mingyang Zhou 28 Dec 30, 2022
Pytorch implementation of DeePSiM

Pytorch implementation of DeePSiM

1 Nov 05, 2021
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".

Graphormer By Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng*, Guolin Ke, Di He*, Yanming Shen and Tie-Yan Liu. This repo is the official impl

Microsoft 1.3k Dec 29, 2022
This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize over continuous domains by Brandon Amos

Tutorial on Amortized Optimization This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize

Meta Research 144 Dec 26, 2022
TResNet: High Performance GPU-Dedicated Architecture

TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I

426 Dec 28, 2022
Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework

MilaGraph 136 Dec 21, 2022
A torch implementation of "Pixel-Level Domain Transfer"

Pixel Level Domain Transfer A torch implementation of "Pixel-Level Domain Transfer". based on dcgan.torch. Dataset The dataset used is "LookBook", fro

Fei Xia 260 Sep 02, 2022
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.

TradingGym TradingGym is a toolkit for training and backtesting the reinforcement learning algorithms. This was inspired by OpenAI Gym and imitated th

Yvictor 1.1k Jan 02, 2023
PyTorch implementation of PSPNet

PSPNet with PyTorch Unofficial implementation of "Pyramid Scene Parsing Network" (https://arxiv.org/abs/1612.01105). This repository is just for caffe

Kazuto Nakashima 52 Nov 16, 2022
ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプル

ByteTrack-ONNX-Sample ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプルです。 ONNXに変換したモデルも同梱しています。 変換自体を試したい方はByteT

KazuhitoTakahashi 16 Oct 26, 2022
Deep universal probabilistic programming with Python and PyTorch

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

7.7k Dec 30, 2022
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an

Microsoft 8k Jan 04, 2023
This repo. is an implementation of ACFFNet, which is accepted for in Image and Vision Computing.

Attention-Guided-Contextual-Feature-Fusion-Network-for-Salient-Object-Detection This repo. is an implementation of ACFFNet, which is accepted for in I

5 Nov 21, 2022
Self-supervised Label Augmentation via Input Transformations (ICML 2020)

Self-supervised Label Augmentation via Input Transformations Authors: Hankook Lee, Sung Ju Hwang, Jinwoo Shin (KAIST) Accepted to ICML 2020 Install de

hankook 96 Dec 29, 2022
BackgroundRemover lets you Remove Background from images and video with a simple command line interface

BackgroundRemover BackgroundRemover is a command line tool to remove background from video and image, made by nadermx to power https://BackgroundRemov

Johnathan Nader 1.7k Dec 30, 2022
Improving the robustness and performance of biomedical NLP models through adversarial training

RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment

Milad Moradi 3 Sep 20, 2022
Monitora la qualità della ricezione dei segnali radio nelle province siciliane.

FMap-server Monitora la qualità della ricezione dei segnali radio nelle province siciliane. Conversion data Frequency - StationName maps are stored in

Triglie 5 May 24, 2021
Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2

CoaDTI Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2 Abstract Environment The test was conducted i

Layne_Huang 7 Nov 14, 2022