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Simulation is an important step in robotics for creating control policies andtesting various physical parameters. Soft robotics is a field that presentsunique physical challenges for simulating its subjects due to the nonlinearityof deformable material components along with other innovative, and oftencomplex, physical properties. Because of the computational cost of simulatingsoft and heterogeneous objects with traditional techniques, rigid roboticssimulators are not well suited to simulating soft robots. Thus, many engineersmust build their own one-off simulators tailored to their system, or useexisting simulators with reduced performance. In order to facilitate thedevelopment of this exciting technology, this work presents aninteractive-speed, accurate, and versatile simulator for a variety of types ofsoft robots. Cronos, our open-source 3D simulation engine, parallelizes amass-spring model for ultra-fast performance on both deformable and rigidobjects. Our approach is applicable to a wide array of nonlinear materialconfigurations, including high deformability, volumetric actuation, orheterogenous stiffness. This versatility provides the ability to mix materialsand geometric components freely within a single robot simulation. By exploitingthe flexibility and scalability of nonlinear Hookean mass-spring systems, thisframework simulates soft and rigid objects via a highly parallel model for nearreal-time speed. We describe an efficient GPU CUDA implementation, which wedemonstrate to achieve computation of over 1 billion elements per second onconsumer-grade GPU cards. Dynamic physical accuracy of the system is validatedby comparing results to Euler-Bernoulli beam theory, natural frequencypredictions, and empirical data of a soft structure under large deformation.

A Massively-Parallel 3D Simulator for Soft and Hybrid Robots