IEEE Robotics & Automation Magazine - September 2023 - 106

SoRoSim
A MATLAB Toolbox for
Hybrid Rigid-Soft Robots
Based on the Geometric
Variable-Strain Approach
By Anup Teejo Mathew ,
Ikhlas Ben Hmida ,
Costanza Armanini
,
Frederic Boyer,
and Federico Renda
Soft robotics has been a trending topic within the robotics community
for almost two decades. However, available tools for the
modeling and analysis of soft robots are still limited. This article
introduces a user-friendly MATLAB toolbox, Soft Robot
Simulator (SoRoSim), that integrates the geometric variablestrain
(GVS) model of Cosserat rods to facilitate the static and
dynamic analysis of soft, rigid, and hybrid robotic systems. We
present a brief overview of the design and structure of the toolbox
and validate it by comparing its results with those published
in the literature. To highlight the toolbox's potential to
efficiently model, simulate, optimize, and control various
robotic systems, we demonstrate four sample applications. The
demonstrated applications explore different actuator and external
loading conditions of single-, branched-, open-, and closedchain
robotic systems. We think that the soft robotics research
community will significantly benefit from the SoRoSim toolbox
for a wide variety of applications.
INTRODUCTION
One of the most trending topics in the robotics community is
the development and design of soft robots that can tackle challenges
otherwise hard and even impossible to solve using their
traditional rigid counterparts [1]. Soft robots are lightweight,
cheap, and adaptable to different environments and scenarios,
Digital Object Identifier 10.1109/MRA.2022.3202488
Date of current version: 20 September 2022
10 IEEE ROBOTICS & AUTOMATION MAGAZINE SEPTEMBER 2023
6
as demonstrated by the vast number of applications where
they have been employed. On the other side, their compliance
and infinite number of degrees of freedom (DoF) intrinsically
increase the complexity of their modeling.
Different modeling approaches have been proposed previously,
varying in their simplifying assumptions and applicability.
Some of the most commonly used approaches in soft
robotics include the lumped mass model (LMM), finite-element
(FEM)-based models, discrete elastic rod (DER) model,
and the piecewise constant curvature (PCC) model. The LMM
assumes soft links to be repeated segments of point masses
connected by springs and dampers corresponding to their
geometry, expected motion, and DoF. FEM-based models provide
a way of numerically approximating partial differential
equations governing the motion and deformation of the soft
body. The PCC model constructs kinematic relations based on
the robot's geometry and behavior under loading by discretizing
its links into a finite number of circular arcs characterized
by constant curvature [2]. Rod models, such as the Euler-Bernoulli
beam, Timoshenko beam, and the Cosserat rod, model
the material deformation of the robot or manipulator by assuming
it to be a 1D continuum mechanics object. The development
of precise theoretical models is crucial, but theory alone may
not be enough to satisfy the demand for computational tools in
the soft robotics field. Knowledge sharing initiatives become
essential to allowing the growth of this relatively new research
field [3]. Generalized modeling platforms eliminate the need to
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commons.org/licenses/by/4.0/
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IEEE Robotics & Automation Magazine - September 2023

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