Bio-inspired artificial vision systems draw inspiration from structural and functional characteristics of natural visual organs to overcome the limitations of conventional camera technologies. Unlike traditional planar imaging systems that rely heavily on complex optics and computational post-processing, bio-inspired imaging platforms can achieve wide field-of-view imaging, reduced optical aberration, enhanced depth perception, and energy-efficient image processing through hardware-level optimization inspired by biological eyes and neural vision pathways. By leveraging the strategies employed by natural vision systems, novel high-performance imaging systems can thereby be developed. Specifically, we have developed a range of AI-native imaging systems inspired by various natural vision systems, including human (^(ⅰ)Nature Nanotechnology, 2022; ^(M)Nature Materials, 2026; ^(ⅱ)Nature Electronics, 2026), fish (^(ⅲ)Nature Electronics, 2020), fiddler crab (^(ⅳ)Nature Electronics, 2022), and cat (^(ⅴ)Science Advances, 2024) vision systems. These artificial vision systems can be integrated with mobile robots such as humanoid robots, submarines, unmanned vehicles, and drones to minimize computational load and latency in edge-level image processing and enable real-time perception and intelligent decision-making in complex environments.