Active Animations of Reduced Deformable Models with Environment Interactions

Abstract

a) (b) (c) Fig. 1. Active deformable animations automatically generated by our approach: A letter T jumping (a), a spider walking (b), and a fish swimming (c). The reduced configuration spaces of these deformable bodies have 5 − 15 DOFs. We present an efficient spacetime optimization formulation that takes into account physics constraints and environmental interactions.We present an efficient spacetime optimization method to automatically generate animations for a general volumetric, elastically deformable body. Our approach can model the interactions between the body and the environment and automatically generate active animations. We model the frictional contact forces using contact invariant optimization and the fluid drag forces using a simplified model. To handle complex objects, we use a reduced deformable model and present a novel hybrid optimizer to search for the local minima efficiently. This allows us to use long-horizon motion planning to automatically generate animations such as walking, jumping, swimming, and rolling. We evaluate the approach on different shapes and animations, including deformable body navigation and combining with an open-loop controller for realtime forward simulation.

Computational Design of Skinned Quad-Robots

“…Barbič et al [68] imposed the equation of motion constraint in elastic body deformation, using the discrete adjoint method to compute the gradients of control forces. Pan et al [71] integrated the contact forces as additional variables to handle environment interactions and solved the spacetime objective with alternating optimization, but did not handle the two-coupling problem we want to solve.…”

Modeling of Deformable Objects for Robotic Manipulation: A Tutorial and Review

“…However, this assumption is valid only when simulating small linear deformations and leads to errors when dynamically simulating large deformations. To overcome this problem, some methods use different formulations of the strain tensor (e.g., the Green strain as in Barbič and James, 2005 ) to enable simulation of larger non-linear deformations (An et al, 2008 ; Pan and Manocha, 2018 ), or adopt more data-driven approaches (e.g., by employing CNNs as in Fulton et al, 2019 ).…”

Locally supported tangential vector,n‐vector, and tensor fields

“…The low computational cost in the online stage, makes subspace methods attractive for interactive graphics applications. Reduced systems have been proposed for the simulation of fluids [TLP06, LMH∗15, CSK18], elastic solids and shells [BJ05, AKJ08, YLX∗15, BEH18], fluid‐solid interaction [LJF16, BSEH19], example‐based elastic material [ZZM15], motion planning [BdSP09, HSvTP12, PM18], clothing [HTC∗14], and hair [CZZ14]. In the context of mesh processing, subspace methods have been introduced for surface modeling [HSL∗06, HSvTP11, JBK∗12, WJBK15], shape interpolation [vTSSH15, vRESH16], injective mappings [HCW19], motion processing [BvTH16], and spectral mesh processing [NBH18].…”