As the core element of adaptive optical systems, tuneable lenses are essential in adaptive optics. Dielectric elastomer-driven tuneable lenses offer significant advantages in tuning range, response speed, and lightweight design compared to traditional mechanical zoom lenses. This paper systematically reviews the working mechanisms and research advancements of these lenses. Firstly, based on the two driving modes of deformation zoom and displacement zoom, the tuning principle of dielectric elastomer-driven tuneable lenses is analysed in depth. Secondly, the design methodology and current status of the research are systematically elaborated for four typical structures: monolithic, composite, array, and metalenses. Finally, the potential applications of this technology are discussed in the fields of auto-zoom imaging, microscopic imaging, augmented reality display, and infrared imaging, along with an analysis of the key technological challenges faced by this technology, such as material properties, modelling and control, preparation processes, and optical performance. This paper aims to provide a systematic reference for researchers in this field and to help promote the engineering application of dielectric elastomer tuneable lens technology.

Compared to traditional mechanical zoom lenses, tunable lenses driven by dielectric elastomers provide clear advantages in zoom range, response speed, and lightweight design. However, these lenses generally employ planar dielectroelastomer actuation, resulting in redundant structures. Additionally, the viscoelastic properties of dielectroelastomer materials often make precise control of focal length difficult. To overcome this issue, this paper introduces a compact, spherical dielectroelastomer-driven tunable lens with a radial size of 20 mm and an effective aperture of 8 mm. A dual-sided actuation structure allows for a 55% adjustment in focal length. Using thermodynamic principles and a spring–viscoelastic rheological model, static and dynamic models of the system have been developed. Experimental results demonstrate that the proposed model accurately predicts the lens’s dynamic response, with a root-mean-square error of less than 0.135, thereby providing a reliable theoretical basis for achieving high-precision focal length control.