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Perovskite retinomorphic image sensor for embodied intelligent vision

Zhilong He, Hongxiao Duan, Jianmin Zeng, Jie Zhou, Xiaolong Zhong, Zhixin Wu, Shenzhou Ni, Ze D. Jiang, Guangjun Xie, Jung‐Yong Lee, Yonghong Zeng, Wu Bin Ying, Zhibin Yang, Zhang Zhang, Gang Liu

Year
2025
Citations
55

Abstract

Retinomorphic systems that can see, recognize, and respond to real-time environmental information will extend the complexity and range of tasks that an exoskeleton robot can perform to better assist physically disabled people. However, the lack of ultrasensitive, reconfigurable, and large-scale integratable retinomorphic devices and advanced edge-processing algorithms makes it difficult to realize retinomorphic hardware. Here, we report the retinomorphic hardware prototype with a 4096-pixel perovskite image sensor array as core module to endow embodied intelligent vision functionalities. The retinomorphic sensor array, using a one photodetector-one transistor geometry to resemble retinal circuit with broadband, ultrahigh, and reconfigurable photoresponsivities, executes both adaptive imaging with a contrast enhancement of ~620% under a dim-lit intensity of 10 microwatts per square centimeter and an instantaneous one-dimensional feature extraction algorithm to decompose the origin visual scenarios into parsimoniously encoded spatiotemporal information. This retinomorphic system endows embodied intelligence with adaptive imaging, in situ processing, and decision-making capabilities and promises enormous potential for autonomous robot applications.

Keywords

Computer scienceRobotArtificial intelligenceComputer visionImage sensorPhotodetectorWearable computerPixelMachine visionImage processing

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