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Photoresponsive liquid crystal elastomer (LCE) plays an important role in soft robotics and other high‐tech fields. The deformation of smart materials directly affects the behavior of the actuator, which needs to be accurately controlled. However, existing control methods for light‐driven LCE actuators often rely on empirical data or simplistic feedback systems, which can be imprecise and susceptible to interference. Developing an accurate and anti‐interference control method for photoresponsive LCE actuators remains a significant challenge. Herein, a computer vision‐assisted light‐driven LCE for accurate control of bending actions of the LCE actuator is proposed. The control system effectively mitigates instability in the bending angle caused by environmental factors such as light, wind, and changes in the surrounding medium. Furthermore, a “lift bridge” for ants moving between two platforms and an oscillator with modulable angular interval and frequency are demonstrated. The proposed system provides a general strategy for accurate and anti‐interference control for photoresponsive LCE actuators, which can be extended to complex actions, multifunctions, and multistimuli actuators, showing wide application potential in soft actuators and soft robots. This article introduces a computer vision‐assisted control strategy for light‐driven liquid crystal elastomer actuators. Through negative feedback regulation, the liquid crystal elastomer actuator exhibits accurate and stable bending deformation in complex environments. The excellent control capability allows the actuator to serve as an ant's “lifting bridge” and an oscillator with modulable angular interval and frequency.

Soft robotics is driving a paradigm shift in conventional rigid robotics by fostering adaptable and safe interactions within dynamic environments. At the forefront of this advancement are liquid crystal elastomer (LCE) actuators, which offer programmable, reversible deformations triggered by various external stimuli. This review provides a comprehensive analysis of LCE actuators, focusing on their alignment strategies, actuation mechanisms, and diverse application potential. Various alignment methods, such as mechanical, external-field (including electric and magnetic), and surface-based techniques, are introduced as effective approaches to tailor mesogen orientation for optimized actuation. Furthermore, we analyze different actuation mechanisms, including heat-, external field-, and light-driven methods, and their distinct advantages for specific applications. The versatility of LCE actuators is showcased through their applications in artificial muscle systems, soft robotic manipulators and grippers, adaptive locomotion, and complex shape-morphing structures. Additionally, this review critically examines the challenges that must be addressed for LCE commercialization, such as manufacturing scalability, mechanical durability, performance optimization, and material safety. Finally, we outline future research directions aimed at overcoming these limitations and unlocking the full potential of LCE technology in next-generation soft robotics. By highlighting the transformative capabilities of LCE actuators, this review underscores their pivotal role in advancing intelligent and reconfigurable robotic l.

Chiral-nematic liquid crystal (N* LC) elastomers exhibit mechano-optical responsive behavior. However, practical sensor applications have been limited by the intrinsic sensitivity of N* LC elastomers to environmental conditions, such as temperature. Although densely cross-linked LC network polymers exhibit high thermal stability, they are not proper for the mechanical sensor due to high glass transition temperatures and low flexibility. To overcome these issues, we focused on enhancing thermal stability by introducing noncovalent cross-linking sites via intermolecular interactions between LC molecules bonded to the polymer network. N* LC elastomers with a cyanobiphenyl derivative as a side-chain mesogen exhibited mechano-optical responsive behavior, with a hypsochromic shift of the reflection peak wavelength under an applied tensile strain and quick shape and color recovery owing to high elasticity. Notably, the N* LC elastomers showed high resistance to harsh environments, including high temperatures and various solvents. Interactions, such as π–π stacking and dipole–dipole interactions, between the cyanobiphenyl units can act as weak cross-links, thus improving the thermal stability of the LC phase without affecting the mechano-optical response. Thus, these N* LC elastomers have great potential for the realization of practical mechano-optical sensors.

Deformable superstructures are man‐made materials with large deformation properties that surpass those of natural materials. However, traditional deformable superstructures generally use conventional materials as substrates, limiting their applications in multi‐mode reconfigurable robots and space‐expandable morphing structures. In this work, amine‐acrylate‐based liquid crystal elastomers (LCEs) are used as deformable superstructures substrate to provide high driving stress and strain. By changing the molar ratio of amine to acrylate, the thermal and mechanical properties of the LCEs are modified. The LCE with a ratio of 0.9 exhibited improved polymerization degree, elongation at break, and toughness. Besides an anisotropic finite deformation model based on hyperelastic theory is developed for the LCEs to capture the configuration variation under temperature activation. Built upon these findings, an LCE‐based paper‐cutting structure with negative Poisson's ratio and a 2D lattice superstructure model are combined, processed, and molded by laser cutting. The developed superstructure is pre‐programmed to the configuration required for service conditions, and the deformation processes are analyzed using both experimental and finite element methods. This study is expected to advance the application of deformable superstructures and LCEs in the fields of defense and military, aerospace, and bionic robotics. Liquid crystal elastomers (LCEs) based on amine‐acrylate chemistry are utilized as the substrate for the development of deformable superstructures. High driving stress and strain are achieved by optimizing the molar ratio of amine and acrylate. Built upon finite element simulation, origami‐inspired and 2D lattice superstructures are developed, exhibiting reversible and controlled deformations.

Natural soft tissue achieves a rich variety of functionality through a hierarchy of molecular, microscale, and mesoscale structures and ordering. Inspired by such architectures, we introduce a soft, multifunctional composite capable of a unique combination of sensing, mechanically robust electronic connectivity, and active shape morphing. The material is composed of a compliant and deformable liquid crystal elastomer (LCE) matrix that can achieve macroscopic shape change through a liquid crystal phase transition. The matrix is dispersed with liquid metal (LM) microparticles that are used to tailor the thermal and electrical conductivity of the LCE without detrimentally altering its mechanical or shape-morphing properties. Demonstrations of this composite for sensing, actuation, circuitry, and soft robot locomotion suggest the potential for versatile, tissue-like multifunctionality.

Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft bodyobstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions.

Programmable shape-shifting materials can take different physical forms to achieve multifunctionality in a dynamic and controllable manner. Although morphing a shape from 2D to 3D via programmed inhomogeneous local deformations has been demonstrated in various ways, the inverse problem—finding how to program a sheet in order for it to take an arbitrary desired 3D shape—is much harder yet critical to realize specific functions. Here, we address this inverse problem in thin liquid crystal elastomer (LCE) sheets, where the shape is preprogrammed by precise and local control of the molecular orientation of the liquid crystal monomers. We show how blueprints for arbitrary surface geometries can be generated using approximate numerical methods and how local extrinsic curvatures can be generated to assist in properly converting these geometries into shapes. Backed by faithfully alignable and rapidly lockable LCE chemistry, we precisely embed our designs in LCE sheets using advanced top-down microfabrication techniques. We thus successfully produce flat sheets that, upon thermal activation, take an arbitrary desired shape, such as a face. The general design principles presented here for creating an arbitrary 3D shape will allow for exploration of unmet needs in flexible electronics, metamaterials, aerospace and medical devices, and more.

Shape-memory materials are smart materials that can remember an original shape and return to their unique state from a deformed secondary shape in the presence of an appropriate stimulus. This property allows these materials to be used as shape-memory artificial muscles, which form a subclass of artificial muscles. The shape-memory artificial muscles are fabricated from shape-memory polymers (SMPs) by twist insertion, shape fixation via Tm or Tg, or by liquid crystal elastomers (LCEs). The prepared SMP artificial muscles can be used in a wide range of applications, from biomimetic and soft robotics to actuators, because they can be operated without sophisticated linkage design and can achieve complex final shapes. Recently, significant achievements have been made in fabrication, modelling, and manipulation of SMP-based artificial muscles. This paper presents a review of the recent progress in shape-memory polymer-based artificial muscles. Here we focus on the mechanisms of SMPs, applications of SMPs as artificial muscles, and the challenges they face concerning actuation. While shape-memory behavior has been demonstrated in several stimulated environments, our focus is on thermal-, photo-, and electrical-actuated SMP artificial muscles.

Photonic actuators, serving as an emerging kind of intelligent stimuli‐responsive material, can exhibit the abilities to change their structural colors/fluorescence and shapes under specific external stimuli, which have demonstrated essential applications in the fields of intelligent soft robotics, sensors, bionics, information storage, anti‐counterfeiting, and energy harvesting. In this review, we reported the state‐of‐the‐art research progress of stimuli‐responsive photonic actuators classified on the basis of the material type and focusing on the actuation mechanisms, design principles, and processing techniques. We also broadly summarized the relative applications of photonic actuators in bionics, intelligent robots, sensors, and so on. Finally, a vision for the challenges in the area and future promising directions of stimuli‐responsive photonic actuators is presented. In this review, the recent progress of stimuli‐responsive photonic actuators with structural color‐/fluorescence color‐changing and shape‐changing capabilities has been systematically presented.

Actuation remains a significant challenge in soft robotics. Actuation by light has important advantages: Objects can be actuated from a distance, distinct frequencies can be used to actuate and control distinct modes with minimal interference, and significant power can be transmitted over long distances through corrosionfree, lightweight fiber optic cables. Photochemical processes that directly convert photons to configurational changes are particularly attractive for actuation. Various works have reported light-induced actuation with liquid crystal elastomers combined with azobenzene photochromes. We present a simple modeling framework and a series of examples that study actuation by light. Of particular interest is the generation of cyclic or periodic motion under steady illumination. We show that this emerges as a result of a coupling between light absorption and deformation. As the structure absorbs light and deforms, the conditions of illumination change, and this, in turn, changes the nature of further deformation. This coupling can be exploited in either closed structures or with structural instabilities to generate cyclic motion.