We present a novel approach for synthesizing liquid sounds directly from visual simulation of fluid dynamics. Our approach takes advantage of the fact that the sound generated by liquid is mainly due to the vibration of resonating bubbles in the medium and performs automatic sound synthesis by coupling physically-based equations for bubble resonance with multiple fluid simulators. We effectively demonstrate our system on several benchmarks using a real-time shallow-water fluid simulator as well as a hybrid grid-SPH simulator.

We present a novel approach to compute collision-free paths for multiple robots subject to local coordination constraints. More specifically, given a set of robots, their initial and final configurations, and possibly some additional coordination constraints, our goal is to compute a collision-free path between the initial and final configuration that maintains the constraints. To solve this problem, our approach generalizes the social potential field method to be applicable to both convex and nonconvex polyhedra. Social potential fields are then integrated into a “physics-based motion planning” framework which uses constrained dynamics to solve the motion planning problem. Our approach is able to plan for over 200 robots while averaging about 110 ms per step in a variety of environments.

We present a method to control the behavior of elastic, deformable material in a dynamic simulation. We introduce dynamic morph targets, the equivalent in dynamic simulation to the geometric morph targets in (quasi-static) modeling. Dynamic morph targets define the pose-dependent physical state of soft objects, including surface deformation and elastic and inertial properties. Given these morph targets, our algorithm then derives a dynamic model that can be simulated in time-pose-space, interpolating the dynamic morph targets at the input poses. Our method easily integrates with current modeling and animation pipelines: at different poses, an artist simply provides a set of dynamic morph targets. Whether these input states are physically plausible is completely up to the artist. The resulting deformable models expose fully dynamic, pose-dependent behavior, driven by the artist-provided morph targets, complete with inertial effects.

Abstract We present a fast goal‐directed motion synthesis technique that integrates sample‐based planning methods with constraint‐based dynamics simulation using a finite element formulation to generate collision‐free paths for deformable models. Our method allows the user to quickly specify various constraints, including a desired trajectory as a sparse sequence of waypoints, and it automatically computes a physically plausible path that satisfies geometric and physical constraints. We demonstrate the performance of our algorithm by computing animated realistic motion of deformable characters and simulation of a medical procedure. Copyright © 2008 John Wiley & Sons, Ltd.