Mechanical metamaterials-enabled soft robots: a review on design, fabrication, actuation, control, and applications

Abstract

Soft robotics has emerged as an important direction in robotics because of its inherent compliance and adaptability. Despite these advantages, conventional soft actuators often remain constrained in design flexibility, functional programmability, and mechanical performance. Mechanical metamaterials—engineered artificial materials whose behavior is governed primarily by geometric architecture rather than intrinsic composition—provide a distinct structural route for addressing these limitations. This review focuses specifically on mechanical metamaterial-enabled soft robots, in which mechanical metamaterial architectures play a defining role in governing deformation, mechanical regulation, and functional performance. In these systems, robotic behavior arises not only from compliant constituent materials, but also from architected geometries capable of generating emergent mechanical properties, such as multistability, auxeticity, and programmable stiffness. From this perspective, the review summarizes recent progress in four closely related aspects: structural design and fabrication, activation of architected mechanical responses, control of metamaterial-mediated behaviors, and representative applications. Particular attention is given to how analytical modeling, finite element analysis, and data-driven inverse design contribute to the programming of architecture-dependent robotic functions; how fabrication strategies support the realization of lattice, origami/kirigami-inspired, and other mechanical metamaterial structures; how different external stimuli activate responses such as buckling, auxetic deformation, and stiffness switching; and how these mechanisms enable functional advances in biomedicine, manipulation, and bioinspired locomotion. These advances indicate that mechanical metamaterials provide an architecture-centered framework for the development of programmable and multifunctional soft robotic systems.