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

TL;DR

SORS delivers a modular FEM-based framework for soft-robotics that unifies nonlinear elasticity, actuation, and contact through three extensible interfaces: energies, forces, and constraints. By solving a constrained energy minimization with SQP and providing Backward Euler and Crank-Nicolson time integration, it achieves high-fidelity simulations that align with real-world behavior. The approach is validated across cantilever, PokeFlex, and a pneumatic soft arm, and demonstrated in a muscle-actuated leg optimization, highlighting strong sim-to-real fidelity and practical utility for control and design. Open-source by design, SORS emphasizes extensibility, reproducibility, and integration with optimization pipelines to accelerate development of next-generation soft robots.

Abstract

The deployment of complex soft robots in multiphysics environments requires advanced simulation frameworks that not only capture interactions between different types of material, but also translate accurately to real-world performance. Soft robots pose unique modeling challenges due to their large nonlinear deformations, material incompressibility, and contact interactions, which complicate both numerical stability and physical accuracy. Despite recent progress, robotic simulators often struggle with modeling such phenomena in a scalable and application-relevant manner. We present SORS (Soft Over Rigid Simulator), a versatile, high-fidelity simulator designed to handle these complexities for soft robot applications. Our energy-based framework, built on the finite element method, 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 showcase the potential of our framework 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 high physical fidelity. By bridging the sim-to-real gap in these challenging domains, our approach provides a validated tool for prototyping next-generation soft robots, filling the gap of extensibility, fidelity, and usability in the soft robotic ecosystem.

Figures (7)

• Figure 1: Next to key physical domains such as actuation, elasticity and contact, a next-gen soft robot introduces unknown physics, underscoring the need for a framework that supports customizable extensions to new physics. Our sim-to-real validated simulator addresses this challenge by enabling extensible modeling across various soft robotic systems. (A) We validate nonlinear material modeling using a cantilever as standard benchmark. (B) We reproduce real-world behavior on a pneumatic soft arm. (C) Our simulator scales up to high-resolution meshes such as tendon-driven helicoid arms (150k DoF).
• Figure 2: Framework architecture of our simulator. On element level, we compute energy terms such as inertia, gravity, and elasticity. On system level, external forces and constraints are evaluated. The user interfaces with the framework by providing custom geometry, physical laws and parameters.
• Figure 3: System identification of passive soft cantilever under varying loads. Here we show one trajectory of a 210g load, matching phase, frequency, and amplitude of real-world data.
• Figure 4: a) End-effector, b) contact cylinder (colored in image as the rod was transparent), and c) indentation area. The sim-to-real comparison demonstrates the ability of our simulator to accurately reproduce contact-induced deformations and overall shape fidelity of highly nonlinear materials.
• Figure 5: System identification of the actuated pneumatic soft arm for six quasistatic tip positions, where each of the six chambers is individually actuated at a pressure of 60kPa.