  Simulation is an important step in robotics for creating control policies and
testing various physical parameters. Soft robotics is a field that presents
unique physical challenges for simulating its subjects due to the nonlinearity
of deformable material components along with other innovative, and often
complex, physical properties. Because of the computational cost of simulating
soft and heterogeneous objects with traditional techniques, rigid robotics
simulators are not well suited to simulating soft robots. Thus, many engineers
must build their own one-off simulators tailored to their system, or use
existing simulators with reduced performance. In order to facilitate the
development of this exciting technology, this work presents an
interactive-speed, accurate, and versatile simulator for a variety of types of
soft robots. Cronos, our open-source 3D simulation engine, parallelizes a
mass-spring model for ultra-fast performance on both deformable and rigid
objects. Our approach is applicable to a wide array of nonlinear material
configurations, including high deformability, volumetric actuation, or
heterogenous stiffness. This versatility provides the ability to mix materials
and geometric components freely within a single robot simulation. By exploiting
the flexibility and scalability of nonlinear Hookean mass-spring systems, this
framework simulates soft and rigid objects via a highly parallel model for near
real-time speed. We describe an efficient GPU CUDA implementation, which we
demonstrate to achieve computation of over 1 billion elements per second on
consumer-grade GPU cards. Dynamic physical accuracy of the system is validated
by comparing results to Euler-Bernoulli beam theory, natural frequency
predictions, and empirical data of a soft structure under large deformation.
