Excitable crawling

TL;DR

This paper introduces a bio-inspired spiking controller based on neural excitability models to enable soft robotic crawlers to achieve autonomous locomotion through rhythmic peristaltic waves, with insights into scale regulation and potential scalability.

Contribution

It presents a novel bistable, spike-generating controller inspired by neural models, integrated with passive crawler mechanics for endogenous crawling behavior.

Findings

Controller achieves rhythmic crawling via proprioceptive feedback.

Geometric analysis elucidates the relationship between electrical and mechanical scales.

Scalability to multiple sensorimotor loops is feasible.

Abstract

We propose and analyze the suitability of a spiking controller to engineer the locomotion of a soft robotic crawler. Inspired by the FitzHugh-Nagumo model of neural excitability, we design a bistable controller with an electrical flipflop circuit representation capable of generating spikes on-demand when coupled to the passive crawler mechanics. A proprioceptive sensory signal from the crawler mechanics turns bistability of the controller into a rhythmic spiking. The output voltage, in turn, activates the crawler's actuators to generate movement through peristaltic waves. We show through geometric analysis that this control strategy achieves endogenous crawling. The electro-mechanical sensorimotor interconnection provides embodied negative feedback regulation, facilitating locomotion. Dimensional analysis provides insights on the characteristic scales in the crawler's mechanical and electrical dynamics, and how they determine the crawling gait. Adaptive control of the electrical scales to optimally match the mechanical scales can be envisioned to achieve further efficiency, as in homeostatic regulation of neuronal circuits. Our approach can scale up to multiple sensorimotor loops inspired by biological central pattern generators.