Developing Simulation Models for Soft Robotic Grippers in Webots

TL;DR

This paper introduces a lightweight, open-source simulation model for a soft robotic gripper within Webots, enabling integrated soft and rigid robot studies using a novel RLD modeling approach validated through experiments.

Contribution

It presents a new RLD-based soft robot simulation model integrated into Webots, bridging the gap between soft and rigid robot simulation environments.

Findings

The RLD model accurately replicates the soft gripper's kinematics and dynamics.

Particle Swarm Optimization effectively identifies model parameters.

Validation experiments confirm the model's efficacy.

Abstract

Robotic simulators provide cost-effective and risk-free virtual environments for studying robotic designs, control algorithms, and sensor integrations. They typically host extensive libraries of sensors and actuators that facilitate rapid prototyping and design evaluations in simulation. The use of the most prominent existing robotic simulators is however limited to simulation of rigid-link robots. On the other hand, there exist dedicated specialized environments for simulating soft robots. This separation limits the study of soft robotic systems, particularly in hybrid scenarios where soft and rigid sub-systems co-exist. In this work, we develop a lightweight open-source digital twin of a commercially available soft gripper, directly integrated within the robotic simulator Webots. We use a Rigid-Link-Discretization (RLD) model to simulate the soft gripper. Using a Particle Swarm Optimization (PSO) approach, we identify the parameters of the RLD model based on the kinematics and dynamics of the physical system and show the efficacy of our modeling approach in validation experiments. All software and experimental details are available on github: https://github.com/anonymousgituser1/Robosoft2025