Snap and Jump: How Elastic Shells Pop Out

TL;DR

This paper investigates the jumping behavior of hemispherical elastic shells driven by snap-buckling, combining experiments, simulations, and analytical theory to understand the complex interplay of elasticity, geometry, and contact friction in soft robotic mechanisms.

Contribution

It provides an analytical model for snap-buckling induced jumping in elastic shells validated by experiments and simulations, advancing the predictive understanding of soft robot dynamics.

Findings

Analytical predictions match experimental and simulation results.

Jumping triggered by contact transition dynamics during snap-buckling.

Complex interplay between elasticity, geometry, and contact friction influences performance.

Abstract

Grip, walk, crawl, and jump. Soft robots are integrated functional structures composed of compliant mechanisms, whose activity spans various industrial applications such as surgery, healthcare, surveillance, and even planetary exploration. One of their promising mobility mechanism is snap-buckling; the instability mode of flexible structures passing from one equilibrium state to another can instantaneously generate large power for its motion. Predicting their performance with even simple geometry requires disentangling material, geometric nonlinearity, and contact, thereby still being a challenging problem to date. Here, we study the jumping dynamics of hemispherical elastic shells driven by snap-buckling, as a model system of soft jumping mechanisms, combining experiments, simulations, and analytical theory. We find that the contact transition dynamics trigger the jumping phenomenon upon snap-buckling by constructing the analytical predictions with shell elasticity in excellent agreement with both experiments and simulations. Despite the simple geometry of the shell, its dynamical performance primarily relies on a complex interplay between elasticity, geometry, and contact friction. By elucidating the dynamics of the building blocks of soft robots that undergo large deformations, we can build their predictive experimental and numerical framework. Our research paves the way for designing soft robots suitable for the required loading conditions or structural requirements without empirical methods.