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Welcome


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Welcome to the Computer Animation Group at RWTH Aachen University!

The research of the Computer Animation Group focuses on physically-based simulation of rigid body systems, deformable solids, and fluids, collision handling, cutting, fracturing, and real-time simulation methods. The main application areas include virtual prototyping, simulation in engineering, medical simulation, computer games and special effects in movies.

News

Best Paper Award

Our paper "Consistent SPH Rigid-Fluid Coupling" got the best paper award at the Eurographics Vision, Modeling, and Visualization 2023.

Sept. 29, 2023

Implicit Density Projection now available on GitHub!

The code for our paper "Implicit Density Projection for Volume Conserving Liquids" has been implemented in the open source project Mantaflow and is now available on GitHub. Check here for the most recent version.

July 27, 2022

Best Paper Award

Our paper "Fast Corotated Elastic SPH Solids with Implicit Zero-Energy Mode Control" got the best paper award at the ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation 2021.

Sept. 10, 2021

Best Paper Award

Our paper "Volume Maps: An Implicit Boundary Representation for SPH" got the best paper award at the ACM SIGGRAPH Motion, Interaction and Games.

Nov. 15, 2019

Best Paper Award

Our paper "A Micropolar Material Model for Turbulent SPH Fluids" got the best paper award at the ACM SIGGRAPH / EUROGRAPHICS Symposium on Computer Animation.

Aug. 15, 2017

SPlisHSPlasH now available on Github!

SPlisHSPlasH is an open-source library for the physically-based simulation of fluids. The simulation in this library is based on the Smoothed Particle Hydrodynamics (SPH) method which is a popular meshless Lagrangian approach to simulate complex fluid effects. Check it out here!

Nov. 17, 2016

Recent Publications

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STARK: A Unified Framework for Strongly Coupled Simulation of Rigid and Deformable Bodies with Frictional Contact

2024 IEEE International Conference on Robotics and Automation (ICRA)

The use of simulation in robotics is increasingly widespread for the purpose of testing, synthetic data generation and skill learning. A relevant aspect of simulation for a variety of robot applications is physics-based simulation of robot-object interactions. This involves the challenge of accurately modeling and implementing different mechanical systems such as rigid and deformable bodies as well as their interactions via constraints, contact or friction. Most state-of-the-art physics engines commonly used in robotics either cannot couple deformable and rigid bodies in the same framework, lack important systems such as cloth or shells, have stability issues in complex friction-dominated setups or cannot robustly prevent penetrations. In this paper, we propose a framework for strongly coupled simulation of rigid and deformable bodies with focus on usability, stability, robustness and easy access to state-of-the-art deformation and frictional contact models. Our system uses the Finite Element Method (FEM) to model deformable solids, the Incremental Potential Contact (IPC) approach for frictional contact and a robust second order optimizer to ensure stable and penetration-free solutions to tight tolerances. It is a general purpose framework, not tied to a particular use case such as grasping or learning, it is written in C++ and comes with a Python interface. We demonstrate our system’s ability to reproduce complex real-world experiments where a mobile vacuum robot interacts with a towel on different floor types and towel geometries. Our system is able to reproduce 100% of the qualitative outcomes observed in the laboratory environment. The simulation pipeline, named Stark (the German word for strong, as in strong coupling) is made open-source.

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Implicit frictional dynamics with soft constraints

IEEE Transactions on Visualization and Computer Graphics

Dynamics simulation with frictional contacts is important for a wide range of applications, from cloth simulation to object manipulation. Recent methods using smoothed lagged friction forces have enabled robust and differentiable simulation of elastodynamics with friction. However, the resulting frictional behavior can be inaccurate and may not converge to analytic solutions. Here we evaluate the accuracy of lagged friction models in comparison with implicit frictional contact systems. We show that major inaccuracies near the stick-slip threshold in such systems are caused by lagging of friction forces rather than by smoothing the Coulomb friction curve. Furthermore, we demonstrate how systems involving implicit or lagged friction can be correctly used with higher-order time integration and highlight limitations in earlier attempts. We demonstrate how to exploit forward-mode automatic differentiation to simplify and, in some cases, improve the performance of the inexact Newton method. Finally, we show that other complex phenomena can also be simulated effectively while maintaining smoothness of the entire system. We extend our method to exhibit stick-slip frictional behavior and preserve volume on compressible and nearly-incompressible media using soft constraints.

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Strongly Coupled Simulation of Magnetic Rigid Bodies

Computer Graphics Forum

We present a strongly coupled method for the robust simulation of linear magnetic rigid bodies. Our approach describes the magnetic effects as part of an incremental potential function. This potential is inserted into the reformulation of the equations of motion for rigid bodies as an optimization problem. For handling collision and friction, we lean on the Incremental Potential Contact (IPC) method. Furthermore, we provide a novel, hybrid explicit / implicit time integration scheme for the magnetic potential based on a distance criterion. This reduces the fill-in of the energy Hessian in cases where the change in magnetic potential energy is small, leading to a simulation speedup without compromising the stability of the system. The resulting system yields a strongly coupled method for the robust simulation of magnetic effects. We showcase the robustness in theory by analyzing the behavior of the magnetic attraction against the contact resolution. Furthermore, we display stability in practice by simulating exceedingly strong and arbitrarily shaped magnets. The results are free of artifacts like bouncing for time step sizes larger than with the equivalent weakly coupled approach. Finally, we showcase the utility of our method in different scenarios with complex joints and numerous magnets.

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