Seeing through arthropod eyes: An AI-assisted, biomimetic approach for high-resolution, multi-task imaging

摘要

Arthropods have intricate compound eyes and optic neuropils, exhibiting exceptional visual capabilities. Combining the strengths of digital imaging with the features of natural arthropod visual systems offers a promising approach to harness wide-angle vision and depth perception while addressing limitations like low resolving power. Here, we present an artificial intelligence-assisted biomimetic system modeled after arthropod vision. We developed a biomimetic compound eye camera with an effective pixel number of 4.3 megapixels capable of producing full-color panoramic images with a viewing angle of 165° and resolving power of 40 micrometers. Using rich visual information, our system achieves high-fidelity image reconstruction, precise 3D position prediction, high-accuracy classification, and pattern recognition through a multistage neural network. Moreover, our compact biomimetic visual system can simultaneously track the 3D motion of multiple miniature targets independently. The proof-of-concept biomimetic arthropod visual system offers a computational panoramic imaging solution, advancing applications in industry, medicine, and robotics.