# Granular Jamming in Soft Robotics: Simulation Frameworks and Emerging Possibilities—Review

## TL;DR

This paper reviews simulation frameworks for granular jamming in soft robotics, highlighting their importance in design and optimization.

## Contribution

The paper provides a comprehensive review of DEM, FEM, and hybrid approaches for simulating granular jamming in soft robotics.

## Key findings

- DEM captures particle-level mechanisms effectively, while FEM is better for system-level optimization.
- Hybrid FEM–DEM approaches offer the highest accuracy but require more computational resources.
- Multiphysics coupling is identified as a key direction for future development in this field.

## Abstract

Soft robotics has become a dynamic field that emphasizes adaptability and safe interaction with complex environments. These structures utilize deformable materials and continuum mechanics to adapt their shape, absorb shocks, and perform tasks in unstructured environments. However, the design and optimization of these systems is challenging, primarily due to the nonlinear and discontinuous behavior of granular materials. In this paper, we address the role of simulation frames as an important tool for understanding, designing, and extending the functionality of software robotic devices utilizing granular jamming. The analysis suggests that DEM is essential for capturing particle-level mechanisms, while FEM is more effective for system-level optimization but tends to smooth out the transition of jamming. Hybrid FEM–DEM approaches provide the highest physical accuracy, albeit at an increased computational cost. Overall, the findings emphasize that the choice of framework must be application-oriented and that multiphysics coupling represents the future development. The review gives an up-do-date review of the simulation tools and approaches for granular-jamming-based systems with a specific focus on continuum arms with a granular-jamming-based central backbone. Such methods can be used for the optimization the back-bone geometry and its filling material (shape, porosity, granule size) with possible use in the real-time control of such arms.