Regulating Airflow Using Hybrid LCN for Soft Pneumatic Circuits

Abstract

Being flexible and adaptive to various environments, soft robotics shows promise as a more robust alternative in many applications compared to traditional, rigid robotics. Of many employable different actuation strategies, pneumatically driven soft robotics have gained attraction owing to their relative straightforward manufacturing and capability to produce significant force to their environment upon interaction. To enable more autonomous pneumatic systems, however, there is an emerging need for developing smarter fluidic elements responding to environmental cues, to provide embodied control and regulation. Herein, a liquid crystal network (LCN)-based fluid regulator is designed to impart stimuli responsiveness and regulation into fluidic circuits by combining radially aligned nematic and nonaligned isotropic LCNs. Assisted by a finite element method, the thermoresponsiveness of the LCN is discussed. Finally, the regulating behavior of the responsive pneumatic regulator is demonstrated, which alters its fluidic resistance with changing temperature. This work emphasizes the potential of advancing responsive soft robotics that can interact with their environment through multiphysical stimuli.