Finite Element Analysis-Based Soft Robotic Modeling: Simulating a Soft Actuator in SOFA

• Published in: IEEE robotics & automation magazine Vol. 31; no. 3; pp. 97 - 105
• Main Authors: Ferrentino, Pasquale, Roels, Ellen, Brancart, Joost, Terryn, Seppe, Van Assche, Guy, Vanderborght, Bram
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Analytical models; Animation; Engineering education; Finite element analysis; Finite element method; Load modeling; Material properties; Mathematical models; Mechanical systems; Mechanics (physics); Modelling; Programming languages; Python; Robotics; Robots; Simulation; Soft robotics; Source code; Tutorials; XML
• ISSN: 1070-9932; 1558-223X
• DOI: 10.1109/MRA.2022.3220536

Soft robotics modeling is a research topic that is evolving fast. Many techniques are present in literature, but most of them require analytical models with a lot of equations that are time consuming, hard to resolve, and not so easy to handle. For this reason, the help of a soft mechanics simulator is essential in this field. This article presents a tutorial on how to build a soft-robot model using an open source finite element analysis (FEA) simulator, called SOFA . This software is able to generate a simulation scene from a code written in Python or XML, so it can be used by people with different fields of competence, like mechanical knowledge, knowledge of material properties, and programming skills. As a case study, a Python simulation of a cable-driven soft actuator that makes contact with a rigid object is considered. The basic working principles of SOFA required to make a scene are explained step by step. In particular, this article shows how to simulate the mechanics and animate the bending behavior of the actuator and the importance of knowledge of the constitutive material properties for good modeling of the mechanical system. Furthermore, we will also show how to retrieve and save data from simulation, demonstrating that SOFA can easily adapt to a multidisciplinary subject, such as research in soft robotics, but can also be useful for teaching simulation and programming language principles to engineering students.