Figure 1: Real-time physics-based quadruped simulations of gaits (walk, trot, canter, transverse gallop, pace, rotary gallop), gait transitions, sitting and standing up, targeted jumps, and jumps on-to and off-of platforms. AbstractWe develop an integrated set of gaits and skills for a physics-based simulation of a quadruped. The motion repertoire for our simulated dog includes walk, trot, pace, canter, transverse gallop, rotary gallop, leaps capable of jumping on-and-off platforms and over obstacles, sitting, lying down, standing up, and getting up from a fall. The controllers use a representation based on gait graphs, a dual leg frame model, a flexible spine model, and the extensive use of internal virtual forces applied via the Jacobian transpose. Optimizations are applied to these control abstractions in order to achieve robust gaits and leaps with desired motion styles. The resulting gaits are evaluated for robustness with respect to push disturbances and the traversal of variable terrain. The simulated motions are also compared to motion data captured from a filmed dog.

Figure 1: Real-time physics-based quadruped simulations of gaits (walk, trot, canter, transverse gallop, pace, rotary gallop), gait transitions, sitting and standing up, targeted jumps, and jumps on-to and off-of platforms. AbstractWe develop an integrated set of gaits and skills for a physics-based simulation of a quadruped. The motion repertoire for our simulated dog includes walk, trot, pace, canter, transverse gallop, rotary gallop, leaps capable of jumping on-and-off platforms and over obstacles, sitting, lying down, standing up, and getting up from a fall. The controllers use a representation based on gait graphs, a dual leg frame model, a flexible spine model, and the extensive use of internal virtual forces applied via the Jacobian transpose. Optimizations are applied to these control abstractions in order to achieve robust gaits and leaps with desired motion styles. The resulting gaits are evaluated for robustness with respect to push disturbances and the traversal of variable terrain. The simulated motions are also compared to motion data captured from a filmed dog.

We present a straightforward, easy-to-implement, point-based approach for animating elastoplastic materials. The core idea of our approach is the introduction of embedded space —the least-squares best fit of the material's rest state into three dimensions. Nearest-neighbor queries in the embedded space efficiently update particle neighborhoods to account for plastic flow. These queries are simpler and more efficient than remeshing strategies employed in mesh-based finite element methods. We also introduce a new estimate for the volume of a particle, allowing particle masses to vary spatially and temporally with fixed density. Our approach can handle simultaneous extreme elastic and plastic deformations. We demonstrate our approach on a variety of examples that exhibit a wide range of material behaviors.

Physics-based animation is often used to animate scenes containing destruction of near-rigid, man-made materials. For these applications, the most important visual features are plastic deformation and fracture. Methods based on continuum mechanics model these materials as elastoplastic, and must perform expensive elasticity computations even though elastic deformations are imperceptibly small for rigid materials. We introduce an example-based plasticity model based on linear blend skinning that allows artists to author simulation objects using familiar tools. Dynamics are computed using an unmodified rigid body simulator, making our method computationally efficient and easy to integrate into existing pipelines. We introduce a flexible technique for mapping impulses computed by the rigid body solver to local, example-based deformations. For completeness, our method also supports prescoring based fracture. We demonstrate the practicality of our method by animating a variety of destructive scenes.

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