Liquid Crystal Polymer‐Based Soft Robots

Yao‐Yu Xiao, Zhi‐Chao Jiang, Yue Zhao

Advanced Intelligent Systems · 2020 · 148 citations · 116 references

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Concepts

TL;DR

Soft robots, particularly those based on liquid crystal polymer networks, surpass conventional robots in safety, adaptability, and continuous deformation due to their large, reversible shape‑changing capabilities developed through extensive synthesis, fabrication, and design research. The article reviews recent advances in LCN soft robots, aiming to provide insights into their design and development. It highlights how stimuli‑responsive LCNs enable intelligent functions such as reprocessability, reconfigurability, self‑regulation, and associative learning in soft robots.

Abstract

Soft robots outperform the conventional robots on enhanced safety for human–machine interaction, environmental adaptability, and continuous deformation. In this blooming area of fundamental and technological importance, liquid crystal polymer networks and liquid crystal elastomers (referred to as LCNs) have emerged as one of the most valuable candidates for soft robots due to their complex, large, and reversible shape change capabilities. To date, much research effort, mainly regarding chemical synthesis, fabrication technologies and soft robot design, has been dedicated to LCN robotic systems to endow them with versatile and complex actions controlled by various stimuli. Herein, starting with the principle that governs the stimuli‐responsiveness of LCNs, recent progress made in LCN soft robots is summarized while focusing on different robotic motions, such as grapping, walking, swimming, and oscillation. Especially, novel LCNs with intelligent functions such as reprocessability, reconfigurability, self‐regulating behavior and associative learning capability, are highlighted. This article aims to provide significant insights into the design and development of LCN‐based soft robots.

References

116