Rational design of a vision fusion system with visible and near-infrared spectral integration for improved environmental perception

合理设计一种结合可见光和近红外光谱的视觉融合系统,以提高环境感知能力

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Abstract

With the rapid advancements in autonomous driving, pure vision-based solutions have garnered significant attention. However, existing vision sensors are limited by their specific spectral operating ranges and the complexity of processing hybrid optical/electrical signals. In this study, we present a fully circuit-emulated vision system that employs a vision fusion solution for autonomous driving, integrating image sensing, fusion, edge extraction, and decision-making functionalities. This system utilizes vision sensors featuring an Al(2)O(3)/two-dimensional Ruddlesden-Popper perovskite (2D PVK) heterostructural dielectric and MoS(2)/black phosphorus (BP)/MoS(2) heterostructural channel, which exhibits persistent nonvolatility and fully light-tunable positive and negative photoresponses when exposed to 1064 nm and 532 nm light, respectively. Notably, when combined with edge extraction circuit design, our vision system achieves all-day visual perception with a 99.0% recognition accuracy for driving scenario information. The integration of the fully circuit-emulated vision system with the vision fusion solution enables a more comprehensive and accurate representation of the driving environment.

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