SORS: A Modular, High-Fidelity Simulator for Soft Robots

The deployment of complex soft robots requires simulation frameworks that not only capture multi-material interactions, but also translate accurately to real-world performance. Soft robots pose unique modeling challenges due to their large nonlinear deformations, near-incompressible materials, and contact interactions, which complicate both numerical stability and physical accuracy. We present SORS†(Soft Over Rigid Simulator), a versatile, high-fidelity simulator designed to handle these complexities for soft robot applications. Our energy-based finite element framework allows modular extensions, enabling the inclusion of custom-designed material and actuation models. To ensure physically consistent contact handling, we integrate a constrained nonlinear optimization based on sequential quadratic programming, allowing for stable and accurate modeling of contact phenomena. We validate our simulator through a diverse set of real-world experiments, which include cantilever deflection, pressure-actuation of a soft robotic arm, and contact interactions from the PokeFlex dataset. In addition, we demonstrate the framework’s utility for control optimization of a soft robotic leg. These tests confirm that our simulator can capture both fundamental material behavior and complex actuation dynamics with physical fidelity. Our approach provides a tool for prototyping next-generation soft robots, filling the gap of extensibility, fidelity, and usability in the soft robotic ecosystem.