Long Yan, Dai Bo, Chang Chenliang, Upreti Neil, Wei Li, Zheng Lulu, Zhuang Songlin, Huang Tony Jun, Zhang Dawei
Engineering Research Center of Optical Instrument and System, the Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China.
Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27709, USA.
Sci Adv. 2025 May 23;11(21):eadt3505. doi: 10.1126/sciadv.adt3505. Epub 2025 May 21.
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.
节肢动物拥有复杂的复眼和视神经节，展现出卓越的视觉能力。将数字成像的优势与自然节肢动物视觉系统的特征相结合，为利用广角视觉和深度感知提供了一种有前景的方法，同时解决了诸如低分辨率等局限性。在此，我们展示了一种以节肢动物视觉为蓝本的人工智能辅助仿生系统。我们开发了一种仿生复眼相机，有效像素数为430万，能够生成视角为165°、分辨率为40微米的全彩全景图像。利用丰富的视觉信息，我们的系统通过多级神经网络实现了高保真图像重建、精确的三维位置预测、高精度分类和模式识别。此外，我们紧凑的仿生视觉系统能够同时独立跟踪多个微型目标的三维运动。这个概念验证的仿生节肢动物视觉系统提供了一种计算全景成像解决方案，推动了在工业、医学和机器人技术中的应用。
