Bioinspired adaptive pupil reflex based on liquid-metal shape-shifters for machine vision

Inspired by the evolutionary diversification of biological eyes for environmental adaptation, recently emerged artificial counterparts offer a variety of visual features that can emulate the eyes of humans, insects, fish, eagles, cats, and others. However, grand challenges reside in developing transformational artificial pupils to address drastic environmental change. Here, we propose a bioinspired vision system that integrates a hemispherical imaging array as an artificial retina with liquid-metal shape-shifters as visual neurons and an adaptive artificial pupil to comprehensively simulate visual recognition with closed-loop pupil reflex behavior. The controlled deformation of the liquid metal allows the design of a range of animal pupil shapes, and the rapid switching of short and open circuits simulates biological spike nerve signals. Under strong light, the system adaptively adjusts the pupil deformation of liquid metal to reduce the amount of exposure, which improves the image recognition accuracy of the artificial vision system under high-light conditions and confirms the key characteristics and functions of the artificial vision system, including ultrawide field of view, adaptive adjustment of light, and image recognition functions. The ability to simulate multiple shapes of animal pupils further demonstrates the programmability of the system and highlights its potential for bioinspired robotic systems, advanced machine vision, and autonomous driving.