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Computer Graphics Forum

Physics simulation is a cornerstone of many computer graphics applications, ranging from video games and virtual reality to visual effects and computational design. The number of techniques for physically-based modeling and animation has thus skyrocketed over the past few decades, facilitating the simulation of a wide variety of materials and physical phenomena. This report captures the state-of-the-art of multiphysics simulation for computer graphics applications. Although a lot of work has focused on simulating individual phenomena, here we put an emphasis on methods developed by the computer graphics community for simulating various physical phenomena and materials, as well as the interactions between them. These include combinations of discretization schemes, mathematical modeling frameworks, and coupling techniques. For the most commonly used methods we provide an overview of the state-of-the-art and deliver valuable insights into the various approaches. A selection of software frameworks that offer out-of-the-box multiphysics modeling capabilities is also presented. Finally, we touch on emerging trends in physics-based animation that affect multiphysics simulation, including machine learning-based methods which have become increasingly popular in recent years.

Robotics and Autonomous Systems

Simulation is a core component of robotics workflows that can shed light on the complex interplay between a physical body, the environment and sensory feedback mechanisms in silico. To this goal several simulation methods, originating in rigid body dynamics and in continuum mechanics have been employed, enabling the simulation of a plethora of phenomena such as rigid/soft body dynamics, fluid dynamics, muscle simulation as well as sensor and actuator dynamics. The physics engines commonly employed in robotics simulation focus on rigid body dynamics, whereas continuum mechanics methods excel on the simulation of phenomena where deformation plays a crucial role, keeping the two fields relatively separate. Here, we propose a shift of paradigm that allows for the accurate simulation of fluids in interaction with rigid bodies within the same robotics simulation framework, based on the continuum mechanics-based Smoothed Particle Hydrodynamics method. The proposed framework is useful for simulations such as swimming robots with complex geometries, robots manipulating fluids and even robots emitting highly viscous materials such as the ones used for 3D printing. Scenarios like swimming on the surface, air-water transitions, locomotion on granular media can be natively simulated within the proposed framework. Firstly, we present the overall architecture of our framework and give examples of a concrete software implementation. We then verify our approach by presenting one of the first of its kind simulation of self-propelled swimming robots with a smooth particle hydrodynamics method and compare our simulations with real experiments. Finally, we propose a new category of simulations that would benefit from this approach and discuss ways that the sim-to-real gap could be further reduced.

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.