We present a differentiable dynamics solver that is able to handle frictional contact for rigid
and deformable objects within a unified framework. Through a principled mollification of …

We present a novel, fast differentiable simulator for soft-body learning and control
applications. Existing differentiable soft-body simulators can be classified into two categories …

Soft robots are primarily composed of soft materials that can allow for mechanically robust
maneuvers that are not typically possible with conventional rigid robotic systems. However …

Digital fabrication devices are powerful tools for creating tangible reproductions of 3D digital
models. Most available printing technologies aim at producing an accurate copy of a …

We introduce Neural Marching Cubes, a data-driven approach for extracting a triangle mesh
from a discretized implicit field. We base our meshing approach on Marching Cubes (MC) …

Compliance is a defining characteristic of biological systems. Understanding how to exploit
soft materials as effectively as living creatures do is consequently a fundamental challenge …

Robots are notoriously difficult to design because of complex interdependencies between
their physical structure, sensory and motor layouts, and behavior. Despite this, almost every …

This paper describes a method for fast simplification of surface meshes. Whereas past
methods focus on visual appearance, our goal is to solve equations on the surface. Hence …

We propose the first reduced model simulation framework for deformable solid dynamics
using autoencoder neural networks. We provide a data‐driven approach to generating …

We propose a comprehensive approach to characterizing the mechanical properties of
structured sheet materials, ie, planar rod networks whose mechanics and aesthetics are …