# Walk the Robot: Exploring Soft Robotic Morphological Communication driven by Spiking Neural Networks

## TL;DR

This paper investigates how soft robots can use their physical dynamics as a communication channel, controlled by spiking neural networks, to improve coordination and control in complex, non-rigid robotic systems.

## Contribution

It demonstrates the emergence of morphological communication in a simulated soft robot driven by spiking neural networks, advancing understanding of dynamic coupling in soft robotics.

## Key findings

- Morphological communication emerges in SNN-controlled soft robots.
- Dynamic coupling enhances robot coordination.
- EvoGym environment facilitates simulation of soft robot behaviors.

## Abstract

Recently, researchers have explored control methods that embrace nonlinear dynamic coupling instead of suppressing it. Such designs leverage dynamical coupling for communication between different parts of the robot. Morphological communication refers to when those dynamics can be used as an emergent data bus to facilitate coordination among independent controller modules within the same robot. Previous research with tensegrity-based robot designs has shown that evolutionary learning models that evolve spiking neural networks (SNN) as robot control mechanisms are effective for controlling non-rigid robots. Our own research explores the emergence of morphological communication in an SNN-based simulated soft robot in theEvoGym environment.