Dynamic Modeling of a Soft Eversion-Based Growing Robot: Physical Analysis, Simulation, and Experimental Validation

Abstract

Soft eversion-based growing robots, also known as vine robots, are a subclass of soft continuum robots that navigate their environment through tip extension-an eversion-based growth mechanism inspired by climbing plants. A deeper understanding of the underlying physics and dynamics of this unique locomotion strategy is crucial for expanding the applicability of soft eversion-based growing robots in complex and constrained environments. Despite their potential, comprehensive dynamic models that capture the full system behavior, including internal pressure dynamics and the pneumatic supply system, remain limited. In this study, we develop a first-principles-based dynamic model of a pressure-driven soft eversion-based growing robot, incorporating both the internal pressure evolution and the flow dynamics of the pneumatic supply system. The proposed model is simulated and experimentally validated on custom-built soft eversion-based growing robots. The proposed model demonstrates excellent predictive capability, achieving a root mean square error (RMSE) of 0.066 m, corresponding to about 5.5% of the final everted length. These findings highlight the critical importance of integrating both pressure and flow dynamics in modeling soft eversion-based growing robots to enable improved control strategies and deeper insight into their physical behavior.