Materials, design, and fabrication of curved image sensors for bio-inspired, AI-friendly vision systems

Robotic vision serves as a crucial sensing modality in perception for artificial intelligence (AI), enabling mobile robots to recognize their environments with human-level intelligence. However, conventional complementary metal–oxide–semiconductor (CMOS) image sensors are not ideal for mobile robotic vision, because their planar form factor necessitates bulky and heavy optical assemblies and power- and time-intensive corrective computations. Bio-inspired vision systems, enabled by the advent of curved image sensors, provide optimal solutions for mobile robotics, enabling AI-friendly imaging functionalities without compromising mobility. In this review, we summarize recent advances in bio-inspired vision systems, with a special focus on curved image sensors and their biologically motivated implementations in robotic vision systems. We first introduce fabrication strategies for curved image sensors—an essential yet technically challenging component of bio-inspired vision systems—in terms of material-level engineering, mechanically compliant device designs, and curved integration techniques. We then review bio-inspired vision systems based on curved image sensors, highlighting their unique optical configurations, advanced imaging functionalities, and AI-integrated robotic applications. Therefore, a system-level framework that connects curvature-enabled optics, mechanically adaptive sensor architectures, and AI-compatible sensing strategies is provided. Finally, we outline the key challenges that hinder the practical deployment of bio-inspired vision systems and discuss promising future research directions toward their integration into mobile robotic platforms.